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Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #1
SelectiveNet: A Deep Neural Network with an Integrated Reject Option
Yonatan Geifman · Ran El-Yaniv
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #2
Manifold Mixup: Better Representations by Interpolating Hidden States
Vikas Verma · Alex Lamb · Christopher Beckham · Amir Najafi · Ioannis Mitliagkas · David Lopez-Paz · Yoshua Bengio
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #3
Processing Megapixel Images with Deep Attention-Sampling Models
Angelos Katharopoulos · Francois Fleuret
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #4
TapNet: Neural Network Augmented with Task-Adaptive Projection for Few-Shot Learning
Sung Whan Yoon · Jun Seo · Jaekyun Moon
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #5
Online Meta-Learning
Chelsea Finn · Aravind Rajeswaran · Sham Kakade · Sergey Levine
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #6
Training Neural Networks with Local Error Signals
Arild Nøkland · Lars Hiller Eidnes
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #7
GMNN: Graph Markov Neural Networks
Meng Qu · Yoshua Bengio · Jian Tang
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #8
Self-Attention Graph Pooling
Junhyun Lee · Inyeop Lee · Jaewoo Kang
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #9
Combating Label Noise in Deep Learning using Abstention
Sunil Thulasidasan · Tanmoy Bhattacharya · Jeff Bilmes · Gopinath Chennupati · Jamal Mohd-Yusof
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #10
LGM-Net: Learning to Generate Matching Networks for Few-Shot Learning
Huaiyu Li · Weiming Dong · Xing Mei · Chongyang Ma · Feiyue Huang · Bao-Gang Hu
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #11
Self-Attention Generative Adversarial Networks
Han Zhang · Ian Goodfellow · Dimitris Metaxas · Augustus Odena
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #12
Multivariate-Information Adversarial Ensemble for Scalable Joint Distribution Matching
Ziliang Chen · ZHANFU YANG · Xiaoxi Wang · Xiaodan Liang · xiaopeng yan · Guanbin Li · Liang Lin
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #13
High-Fidelity Image Generation With Fewer Labels
Mario Lucic · Michael Tschannen · Marvin Ritter · Xiaohua Zhai · Olivier Bachem · Sylvain Gelly
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #14
Revisiting precision recall definition for generative modeling
Loic Simon · Ryan Webster · Julien Rabin
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #15
Wasserstein of Wasserstein Loss for Learning Generative Models
Yonatan Dukler · Wuchen Li · Alex Lin · Guido Montufar
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #16
Flat Metric Minimization with Applications in Generative Modeling
Thomas Möllenhoff · Daniel Cremers
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #17
Entropic GANs meet VAEs: A Statistical Approach to Compute Sample Likelihoods in GANs
Yogesh Balaji · Hamed Hassani · Rama Chellappa · Soheil Feizi
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #18
Non-Parametric Priors For Generative Adversarial Networks
Rajhans Singh · Pavan Turaga · Suren Jayasuriya · Ravi Garg · Martin Braun
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #19
Lipschitz Generative Adversarial Nets
Zhiming Zhou · Jiadong Liang · Yuxuan Song · Lantao Yu · Hongwei Wang · Weinan Zhang · Yong Yu · Zhihua Zhang
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #20
HexaGAN: Generative Adversarial Nets for Real World Classification
Uiwon Hwang · Dahuin Jung · Sungroh Yoon
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #21
Graph Matching Networks for Learning the Similarity of Graph Structured Objects
Yujia Li · Chenjie Gu · Thomas Dullien · Oriol Vinyals · Pushmeet Kohli
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #22
BayesNAS: A Bayesian Approach for Neural Architecture Search
Hongpeng Zhou · Minghao Yang · Jun Wang · Wei Pan
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #23
Set Transformer: A Framework for Attention-based Permutation-Invariant Neural Networks
Juho Lee · Yoonho Lee · Jungtaek Kim · Adam Kosiorek · Seungjin Choi · Yee Whye Teh
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #24
Shallow-Deep Networks: Understanding and Mitigating Network Overthinking
Yigitcan Kaya · Sanghyun Hong · Tudor Dumitras
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #25
Graph U-Nets
Hongyang Gao · Shuiwang Ji
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #26
SATNet: Bridging deep learning and logical reasoning using a differentiable satisfiability solver
Po-Wei Wang · Priya Donti · Bryan Wilder · Zico Kolter
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #27
Area Attention
Yang Li · Lukasz Kaiser · Samy Bengio · Si Si
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #28
The Evolved Transformer
David So · Quoc Le · Chen Liang
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #29
Jumpout : Improved Dropout for Deep Neural Networks with ReLUs
Shengjie Wang · Tianyi Zhou · Jeff Bilmes
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #30
Stochastic Deep Networks
Gwendoline De Bie · Gabriel Peyré · Marco Cuturi
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #31
ELF OpenGo: an analysis and open reimplementation of AlphaZero
Yuandong Tian · Jerry Ma · Qucheng Gong · Shubho Sengupta · Zhuoyuan Chen · James Pinkerton · Larry Zitnick
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #32
Making Deep Q-learning methods robust to time discretization
Corentin Tallec · Leonard Blier · Yann Ollivier
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #33
Nonlinear Distributional Gradient Temporal-Difference Learning
chao qu · Shie Mannor · Huan Xu
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #34
Composing Entropic Policies using Divergence Correction
Jonathan Hunt · Andre Barreto · Timothy Lillicrap · Nicolas Heess
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #35
TibGM: A Transferable and Information-Based Graphical Model Approach for Reinforcement Learning
Tameem Adel · Adrian Weller
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #36
Multi-Agent Adversarial Inverse Reinforcement Learning
Lantao Yu · Jiaming Song · Stefano Ermon
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #37
Policy Consolidation for Continual Reinforcement Learning
Christos Kaplanis · Murray Shanahan · Claudia Clopath
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #38
Off-Policy Deep Reinforcement Learning without Exploration
Scott Fujimoto · David Meger · Doina Precup
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #39
Random Expert Distillation: Imitation Learning via Expert Policy Support Estimation
Ruohan Wang · Carlo Ciliberto · Pierluigi Vito Amadori · Yiannis Demiris
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #40
Revisiting the Softmax Bellman Operator: New Benefits and New Perspective
Zhao Song · Ron Parr · Lawrence Carin
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #41
An Investigation of Model-Free Planning
Arthur Guez · Mehdi Mirza · Karol Gregor · Rishabh Kabra · Sebastien Racaniere · Theophane Weber · David Raposo · Adam Santoro · Laurent Orseau · Tom Eccles · Greg Wayne · David Silver · Timothy Lillicrap
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #42
CURIOUS: Intrinsically Motivated Modular Multi-Goal Reinforcement Learning
Cédric Colas · Pierre-Yves Oudeyer · Olivier Sigaud · Pierre Fournier · Mohamed Chetouani
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #43
Task-Agnostic Dynamics Priors for Deep Reinforcement Learning
Yilun Du · Karthik Narasimhan
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #44
Diagnosing Bottlenecks in Deep Q-learning Algorithms
Justin Fu · Aviral Kumar · Matthew Soh · Sergey Levine
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #45
Collaborative Evolutionary Reinforcement Learning
Shauharda Khadka · Somdeb Majumdar · Tarek Nassar · Zach Dwiel · Evren Tumer · Santiago Miret · Yinyin Liu · Kagan Tumer
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #46
EMI: Exploration with Mutual Information
Hyoungseok Kim · Jaekyeom Kim · Yeonwoo Jeong · Sergey Levine · Hyun Oh Song
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #47
Imitation Learning from Imperfect Demonstration
Yueh-Hua Wu · Nontawat Charoenphakdee · Han Bao · Voot Tangkaratt · Masashi Sugiyama
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #48
Curiosity-Bottleneck: Exploration By Distilling Task-Specific Novelty
Youngjin Kim · Daniel Nam · Hyunwoo Kim · Ji-Hoon Kim · Gunhee Kim
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #49
Dynamic Weights in Multi-Objective Deep Reinforcement Learning
Axel Abels · Diederik Roijers · Tom Lenaerts · Ann Nowé · Denis Steckelmacher
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #50
Fingerprint Policy Optimisation for Robust Reinforcement Learning
Supratik Paul · Michael A Osborne · Shimon Whiteson
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #51
An Investigation into Neural Net Optimization via Hessian Eigenvalue Density
Behrooz Ghorbani · Shankar Krishnan · Ying Xiao
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #52
Differentiable Linearized ADMM
Xingyu Xie · Jianlong Wu · Guangcan Liu · Zhisheng Zhong · Zhouchen Lin
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #53
Adaptive Stochastic Natural Gradient Method for One-Shot Neural Architecture Search
Youhei Akimoto · Shinichi Shirakawa · Nozomu Yoshinari · Kento Uchida · Shota Saito · Kouhei Nishida
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #54
A Quantitative Analysis of the Effect of Batch Normalization on Gradient Descent
YongQiang Cai · Qianxiao Li · Zuowei Shen
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #55
The Effect of Network Width on Stochastic Gradient Descent and Generalization: an Empirical Study
Daniel Park · Jascha Sohl-Dickstein · Quoc Le · Samuel L Smith
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #56
AdaGrad stepsizes: sharp convergence over nonconvex landscapes
Rachel Ward · Xiaoxia Wu · Leon Bottou
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #57
Beyond Backprop: Online Alternating Minimization with Auxiliary Variables
Anna Choromanska · Benjamin Cowen · Sadhana Kumaravel · Ronny Luss · Mattia Rigotti · Irina Rish · Paolo DiAchille · Viatcheslav Gurev · Brian Kingsbury · Ravi Tejwani · Djallel Bouneffouf
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #58
SWALP : Stochastic Weight Averaging in Low Precision Training
Guandao Yang · Tianyi Zhang · Polina Kirichenko · Junwen Bai · Andrew Wilson · Chris De Sa
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #59
Efficient optimization of loops and limits with randomized telescoping sums
Alex Beatson · Ryan P Adams
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #60
Self-similar Epochs: Value in arrangement
Eliav Buchnik · Edith Cohen · Avinatan Hasidim · Yossi Matias
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #61
Adversarial Attacks on Node Embeddings via Graph Poisoning
Aleksandar Bojchevski · Stephan Günnemann
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #62
First-Order Adversarial Vulnerability of Neural Networks and Input Dimension
Carl-Johann Simon-Gabriel · Yann Ollivier · Leon Bottou · Bernhard Schölkopf · David Lopez-Paz
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #63
On Certifying Non-Uniform Bounds against Adversarial Attacks
Chen Liu · Ryota Tomioka · Volkan Cevher
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #64
Improving Adversarial Robustness via Promoting Ensemble Diversity
Tianyu Pang · Kun Xu · Chao Du · Ning Chen · Jun Zhu
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #65
Adversarial camera stickers: A physical camera-based attack on deep learning systems
Juncheng Li · Frank Schmidt · Zico Kolter
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #66
Adversarial examples from computational constraints
Sebastien Bubeck · Yin Tat Lee · Eric Price · Ilya Razenshteyn
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #67
POPQORN: Quantifying Robustness of Recurrent Neural Networks
CHING-YUN KO · Zhaoyang Lyu · Tsui-Wei Weng · Luca Daniel · Ngai Wong · Dahua Lin
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #68
Using Pre-Training Can Improve Model Robustness and Uncertainty
Dan Hendrycks · Kimin Lee · Mantas Mazeika
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #69
Generalized No Free Lunch Theorem for Adversarial Robustness
Elvis Dohmatob
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #70
PROVEN: Verifying Robustness of Neural Networks with a Probabilistic Approach
Tsui-Wei Weng · Pin-Yu Chen · Lam Nguyen · Mark Squillante · Akhilan Boopathy · Ivan Oseledets · Luca Daniel
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #71
On Learning Invariant Representations for Domain Adaptation
Han Zhao · Remi Tachet des Combes · Kun Zhang · Geoff Gordon
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #72
Lexicographic and Depth-Sensitive Margins in Homogeneous and Non-Homogeneous Deep Models
Mor Shpigel Nacson · Suriya Gunasekar · Jason Lee · Nati Srebro · Daniel Soudry
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #73
Adversarial Generation of Time-Frequency Features with application in audio synthesis
Andrés Marafioti · Nathanaël Perraudin · Nicki Holighaus · Piotr Majdak
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #74
On the Universality of Invariant Networks
Haggai Maron · Ethan Fetaya · Nimrod Segol · Yaron Lipman
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #75
Fine-Grained Analysis of Optimization and Generalization for Overparameterized Two-Layer Neural Networks
Sanjeev Arora · Simon Du · Wei Hu · Zhiyuan Li · Ruosong Wang
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #76
Gauge Equivariant Convolutional Networks and the Icosahedral CNN
Taco Cohen · Maurice Weiler · Berkay Kicanaoglu · Max Welling
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #77
Feature-Critic Networks for Heterogeneous Domain Generalization
Yiying Li · Yongxin Yang · Wei Zhou · Timothy Hospedales
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #78
Learning to Convolve: A Generalized Weight-Tying Approach
Nichita Diaconu · Daniel E Worrall
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #79
On Dropout and Nuclear Norm Regularization
Poorya Mianjy · Raman Arora
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #80
Gradient Descent Finds Global Minima of Deep Neural Networks
Simon Du · Jason Lee · Haochuan Li · Liwei Wang · Xiyu Zhai
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #81
Composable Core-sets for Determinant Maximization: A Simple Near-Optimal Algorithm
Sepideh Mahabadi · Piotr Indyk · Shayan Oveis Gharan · Alireza Rezaei
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #82
Sublinear Time Nearest Neighbor Search over Generalized Weighted Space
Yifan Lei · Qiang Huang · Mohan Kankanhalli · Anthony Tung
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #83
Compressing Gradient Optimizers via Count-Sketches
Ryan Spring · Anastasios Kyrillidis · Vijai Mohan · Anshumali Shrivastava
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #84
Scalable Fair Clustering
Arturs Backurs · Piotr Indyk · Krzysztof Onak · Baruch Schieber · Ali Vakilian · Tal Wagner
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #85
Conditional Gradient Methods via Stochastic Path-Integrated Differential Estimator
Alp Yurtsever · Suvrit Sra · Volkan Cevher
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #86
Fault Tolerance in Iterative-Convergent Machine Learning
Aurick Qiao · Bryon Aragam · Bingjing Zhang · Eric Xing
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #87
Static Automatic Batching In TensorFlow
Ashish Agarwal
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #88
Improving Neural Network Quantization without Retraining using Outlier Channel Splitting
Ritchie Zhao · Yuwei Hu · Jordan Dotzel · Chris De Sa · Zhiru Zhang
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #89
Memory-Optimal Direct Convolutions for Maximizing Classification Accuracy in Embedded Applications
Albert Gural · Boris Murmann
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #90
DL2: Training and Querying Neural Networks with Logic
Marc Fischer · Mislav Balunovic · Dana Drachsler-Cohen · Timon Gehr · Ce Zhang · Martin Vechev
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #91
PA-GD: On the Convergence of Perturbed Alternating Gradient Descent to Second-Order Stationary Points for Structured Nonconvex Optimization
Songtao Lu · Mingyi Hong · Zhengdao Wang
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #92
Improved Zeroth-Order Variance Reduced Algorithms and Analysis for Nonconvex Optimization
Kaiyi Ji · Zhe Wang · Yi Zhou · Yingbin LIANG
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #93
Faster Stochastic Alternating Direction Method of Multipliers for Nonconvex Optimization
Feihu Huang · Songcan Chen · Heng Huang
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #94
Lower Bounds for Smooth Nonconvex Finite-Sum Optimization
Dongruo Zhou · Quanquan Gu
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #95
Nonconvex Variance Reduced Optimization with Arbitrary Sampling
Samuel Horvath · Peter Richtarik
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #96
Error Feedback Fixes SignSGD and other Gradient Compression Schemes
Sai Praneeth Reddy Karimireddy · Quentin Rebjock · Sebastian Stich · Martin Jaggi
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #97
A Composite Randomized Incremental Gradient Method
Junyu Zhang · Lin Xiao
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #98
Optimal Continuous DR-Submodular Maximization and Applications to Provable Mean Field Inference
Yatao (An) Bian · Joachim Buhmann · Andreas Krause
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #99
Multiplicative Weights Updates as a distributed constrained optimization algorithm: Convergence to second-order stationary points almost always
Ioannis Panageas · Georgios Piliouras · xiao wang
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #100
Katalyst: Boosting Convex Katayusha for Non-Convex Problems with a Large Condition Number
Zaiyi Chen · Yi Xu · Haoyuan Hu · Tianbao Yang
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #101
Safe Policy Improvement with Baseline Bootstrapping
Romain Laroche · Paul TRICHELAIR · Remi Tachet des Combes
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #102
Distributional Reinforcement Learning for Efficient Exploration
Borislav Mavrin · Hengshuai Yao · Linglong Kong · Kaiwen Wu · Yaoliang Yu
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #103
Optimistic Policy Optimization via Multiple Importance Sampling
Matteo Papini · Alberto Maria Metelli · Lorenzo Lupo · Marcello Restelli
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #104
Neural Logic Reinforcement Learning
zhengyao jiang · Shan Luo
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #105
Learning to Collaborate in Markov Decision Processes
Goran Radanovic · Rati Devidze · David Parkes · Adish Singla
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #106
Predictor-Corrector Policy Optimization
Ching-An Cheng · Xinyan Yan · Nathan Ratliff · Byron Boots
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #107
Learning a Prior over Intent via Meta-Inverse Reinforcement Learning
Kelvin Xu · Ellis Ratner · EECS Anca Dragan · Sergey Levine · Chelsea Finn
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #108
DeepMDP: Learning Continuous Latent Space Models for Representation Learning
Carles Gelada · Saurabh Kumar · Jacob Buckman · Ofir Nachum · Marc Bellemare
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #109
Importance Sampling Policy Evaluation with an Estimated Behavior Policy
Josiah Hanna · Scott Niekum · Peter Stone
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #110
Learning from a Learner
alexis jacq · Matthieu Geist · Ana Paiva · Olivier Pietquin
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #111
Separable value functions across time-scales
Joshua Romoff · Peter Henderson · Ahmed Touati · Yann Ollivier · Joelle Pineau · Emma Brunskill
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #112
Learning Action Representations for Reinforcement Learning
Yash Chandak · Georgios Theocharous · James Kostas · Scott Jordan · Philip Thomas
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #113
Bayesian Counterfactual Risk Minimization
Ben London · Ted Sandler
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #114
Per-Decision Option Discounting
Anna Harutyunyan · Peter Vrancx · Philippe Hamel · Ann Nowe · Doina Precup
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #115
Tighter Problem-Dependent Regret Bounds in Reinforcement Learning without Domain Knowledge using Value Function Bounds
Andrea Zanette · Emma Brunskill
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #116
A Theory of Regularized Markov Decision Processes
Matthieu Geist · Bruno Scherrer · Olivier Pietquin
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #117
Discovering Options for Exploration by Minimizing Cover Time
Yuu Jinnai · Jee Won Park · David Abel · George Konidaris
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #118
Policy Certificates: Towards Accountable Reinforcement Learning
Christoph Dann · Lihong Li · Wei Wei · Emma Brunskill
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #119
The Value Function Polytope in Reinforcement Learning
Robert Dadashi · Marc Bellemare · Adrien Ali Taiga · Nicolas Le Roux · Dale Schuurmans
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #120
Data Shapley: Equitable Valuation of Data for Machine Learning
Amirata Ghorbani · James Zou
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #121
Feature Grouping as a Stochastic Regularizer for High-Dimensional Structured Data
Sergul Aydore · Thirion Bertrand · Gael Varoquaux
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #122
Metric-Optimized Example Weights
Sen Zhao · Mahdi Milani Fard · Harikrishna Narasimhan · Maya Gupta
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #123
Improving Model Selection by Employing the Test Data
Max Westphal · Werner Brannath
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #124
Topological Data Analysis of Decision Boundaries with Application to Model Selection
Karthikeyan Ramamurthy · Kush Varshney · Krishnan Mody
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #125
Contextual Memory Trees
Wen Sun · Alina Beygelzimer · Hal Daume · John Langford · Paul Mineiro
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #126
Sparse Extreme Multi-label Learning with Oracle Property
Weiwei Liu · Xiaobo Shen
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #127
Shape Constraints for Set Functions
Andrew Cotter · Maya Gupta · Heinrich Jiang · Erez Louidor · James Muller · Tamann Narayan · Serena Wang · Tao Zhu
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #128
On The Power of Curriculum Learning in Training Deep Networks
Guy Hacohen · Daphna Weinshall
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #129
Voronoi Boundary Classification: A High-Dimensional Geometric Approach via Weighted Monte Carlo Integration
Vladislav Polianskii · Florian Pokorny
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #130
Robust Decision Trees Against Adversarial Examples
Hongge Chen · Huan Zhang · Duane Boning · Cho-Jui Hsieh
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #131
Automatic Classifiers as Scientific Instruments: One Step Further Away from Ground-Truth
Jacob Whitehill · Anand Ramakrishnan
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #132
Look Ma, No Latent Variables: Accurate Cutset Networks via Compilation
Tahrima Rahman · Shasha Jin · Vibhav Gogate
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #133
Optimal Transport for structured data with application on graphs
Titouan Vayer · Nicolas Courty · Romain Tavenard · Chapel Laetitia · Remi Flamary
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #134
Learning Optimal Linear Regularizers
Matthew Streeter
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #135
On Symmetric Losses for Learning from Corrupted Labels
Nontawat Charoenphakdee · Jongyeong Lee · Masashi Sugiyama
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #136
AUCµ: A Performance Metric for Multi-Class Machine Learning Models
Ross Kleiman · University of Wisconsin David Page
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #137
Regularization in directable environments with application to Tetris
Jan Malte Lichtenberg · Ozgur Simsek
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #138
Improved Dynamic Graph Learning through Fault-Tolerant Sparsification
Chunjiang Zhu · Sabine Storandt · Kam-Yiu Lam · Song Han · Jinbo Bi
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #139
Heterogeneous Model Reuse via Optimizing Multiparty Multiclass Margin
Xi-Zhu Wu · Song Liu · Zhi-Hua Zhou
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #140
Rethinking Lossy Compression: The Rate-Distortion-Perception Tradeoff
Yochai Blau · Tomer Michaeli
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #141
Collaborative Channel Pruning for Deep Networks
Hanyu Peng · Jiaxiang Wu · Shifeng Chen · Junzhou Huang
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #142
Same, Same But Different: Recovering Neural Network Quantization Error Through Weight Factorization
Eldad Meller · Alexander Finkelstein · Uri Almog · Mark Grobman
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #143
GDPP: Learning Diverse Generations using Determinantal Point Processes
Mohamed Elfeki · Camille Couprie · Morgane Riviere · Mohamed Elhoseiny
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #144
Co-Representation Network for Generalized Zero-Shot Learning
Fei Zhang · Guangming Shi
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #145
GEOMetrics: Exploiting Geometric Structure for Graph-Encoded Objects
Edward Smith · Adriana Romero · Scott Fujimoto · David Meger
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #146
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
Mingxing Tan · Quoc Le
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #147
Geometry Aware Convolutional Filters for Omnidirectional Images Representation
Renata Khasanova · Pascal Frossard
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #148
A Personalized Affective Memory Model for Improving Emotion Recognition
Pablo Barros · German Parisi · Stefan Wermter
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #149
Temporal Gaussian Mixture Layer for Videos
AJ Piergiovanni · Michael Ryoo
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #150
Regret Circuits: Composability of Regret Minimizers
Gabriele Farina · Christian Kroer · Tuomas Sandholm
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #151
Game Theoretic Optimization via Gradient-based Nikaido-Isoda Function
Arvind Raghunathan · Anoop Cherian · Devesh Jha
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #152
Stable-Predictive Optimistic Counterfactual Regret Minimization
Gabriele Farina · Christian Kroer · Noam Brown · Tuomas Sandholm
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #153
When Samples Are Strategically Selected
Hanrui Zhang · Yu Cheng · Vincent Conitzer
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #154
Statistical Foundations of Virtual Democracy
Anson Kahng · Min Kyung Lee · Ritesh Noothigattu · Ariel Procaccia · Christos-Alexandros Psomas
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #155
Optimal Auctions through Deep Learning
Paul Duetting · Zhe Feng · Harikrishna Narasimhan · David Parkes · Sai Srivatsa Ravindranath
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #156
Learning to Clear the Market
Weiran Shen · Sébastien Lahaie · Renato Leme
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #157
Learning to bid in revenue-maximizing auctions
Thomas Nedelec · Noureddine El Karoui · Vianney Perchet
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #158
Open-ended learning in symmetric zero-sum games
David Balduzzi · Marta Garnelo · Yoram Bachrach · Wojciech Czarnecki · Julien Perolat · Max Jaderberg · Thore Graepel
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #159
Deep Counterfactual Regret Minimization
Noam Brown · Adam Lerer · Sam Gross · Tuomas Sandholm
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #160
Generalized Approximate Survey Propagation for High-Dimensional Estimation
Carlo Lucibello · Luca Saglietti · Yue Lu
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #161
Boosted Density Estimation Remastered
Zac Cranko · Richard Nock
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #162
Inference and Sampling of $K_{33}$-free Ising Models
Valerii Likhosherstov · Yury Maximov · Misha Chertkov
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #163
Random Matrix Improved Covariance Estimation for a Large Class of Metrics
Malik TIOMOKO A · Romain Couillet · Florent BOUCHARD · Guillaume GINOLHAC
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #164
Dual Entangled Polynomial Code: Three-Dimensional Coding for Distributed Matrix Multiplication
Pedro Soto · Jun Li · Xiaodi Fan
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #165
Neural Joint Source-Channel Coding
Kristy Choi · Kedar Tatwawadi · Aditya Grover · Tsachy Weissman · Stefano Ermon
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #166
Doubly-Competitive Distribution Estimation
Yi Hao · Alon Orlitsky
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #167
Homomorphic Sensing
Manolis Tsakiris · Liangzu Peng
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #168
Phaseless PCA: Low-Rank Matrix Recovery from Column-wise Phaseless Measurements
Seyedehsara Nayer · Praneeth Narayanamurthy · Namrata Vaswani
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #169
Rate Distortion For Model Compression:From Theory To Practice
Weihao Gao · Yu-Han Liu · Chong Wang · Sewoong Oh
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #170
Formal Privacy for Functional Data with Gaussian Perturbations
Ardalan Mirshani · Matthew Reimherr · Aleksandra Slavković
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #171
Graphical-model based estimation and inference for differential privacy
Ryan McKenna · Daniel Sheldon · Gerome Miklau
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #172
White-box vs Black-box: Bayes Optimal Strategies for Membership Inference
Alexandre Sablayrolles · Douze Matthijs · Cordelia Schmid · Yann Ollivier · Herve Jegou
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #173
An Optimal Private Stochastic-MAB Algorithm based on Optimal Private Stopping Rule
Touqir Sajed · Or Sheffet
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #174
Sublinear Space Private Algorithms Under the Sliding Window Model
Jalaj Upadhyay
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #175
Locally Private Bayesian Inference for Count Models
Aaron Schein · Zhiwei Steven Wu · Alexandra Schofield · Mingyuan Zhou · Hanna Wallach
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #176
Low Latency Privacy Preserving Inference
Alon Brutzkus · Ran Gilad-Bachrach · Oren Elisha
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #177
Communication Complexity in Locally Private Distribution Estimation and Heavy Hitters
Jayadev Acharya · Ziteng Sun
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #178
Poission Subsampled R\'enyi Differential Privacy
Yuqing Zhu · Yu-Xiang Wang
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #179
Benefits and Pitfalls of the Exponential Mechanism with Applications to Hilbert Spaces and Functional PCA
Jordan Awan · Ana Kenney · Matthew Reimherr · Aleksandra Slavković
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #180
Refined Complexity of PCA with Outliers
Kirill Simonov · Fedor Fomin · Petr Golovach · Fahad Panolan
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #181
On Efficient Optimal Transport: An Analysis of Greedy and Accelerated Mirror Descent Algorithms
Tianyi Lin · Nhat Ho · Michael Jordan
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #182
Passed & Spurious: Descent Algorithms and Local Minima in Spiked Matrix-Tensor Models
Stefano Sarao Mannelli · Florent Krzakala · Pierfrancesco Urbani · Lenka Zdeborova
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #183
Teaching a black-box learner
Sanjoy Dasgupta · Daniel Hsu · Stefanos Poulis · Jerry Zhu
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #184
PAC Learnability of Node Functions in Networked Dynamical Systems
Abhijin Adiga · Chris J Kuhlman · Madhav Marathe · S. S. Ravi · Anil Vullikanti
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #185
Online learning with kernel losses
Niladri S Chatterji · Aldo Pacchiano · Peter Bartlett
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #186
Nearest Neighbor and Kernel Survival Analysis: Nonasymptotic Error Bounds and Strong Consistency Rates
George Chen
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #187
Fast Rates for a kNN Classifier Robust to Unknown Asymmetric Label Noise
Henry Reeve · Ata Kaban
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #188
Uniform Convergence Rate of the Kernel Density Estimator Adaptive to Intrinsic Volume Dimension
Jisu Kim · Jaehyeok Shin · Alessandro Rinaldo · Larry Wasserman
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #189
Maximum Likelihood Estimation for Learning Populations of Parameters
Ramya Korlakai Vinayak · Weihao Kong · Gregory Valiant · Sham Kakade
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #190
Projection onto Minkowski Sums with Application to Constrained Learning
Joong-Ho Won · Jason Xu · Kenneth Lange
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #191
Blended Conditonal Gradients
Gábor Braun · Sebastian Pokutta · Dan Tu · Stephen Wright
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #192
Acceleration of SVRG and Katyusha X by Inexact Preconditioning
Yanli Liu · Fei Feng · Wotao Yin
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #193
Characterization of Convex Objective Functions and Optimal Expected Convergence Rates for SGD
Marten van Dijk · Lam Nguyen · PHUONG_HA NGUYEN · Dzung Phan
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #194
A Conditional-Gradient-Based Augmented Lagrangian Framework
Alp Yurtsever · Olivier Fercoq · Volkan Cevher
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #195
SGD: General Analysis and Improved Rates
Robert M. Gower · Nicolas Loizou · Xun Qian · Alibek Sailanbayev · Egor Shulgin · Peter Richtarik
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #196
Curvature-Exploiting Acceleration of Elastic Net Computations
Vien Van Mai · Mikael Johansson
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #197
Decentralized Stochastic Optimization and Gossip Algorithms with Compressed Communication
Anastasiia Koloskova · Sebastian Stich · Martin Jaggi
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom
Safe Grid Search with Optimal Complexity
Eugene Ndiaye · Tam Le · Olivier Fercoq · Joseph Salmon · Ichiro Takeuchi
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #199
SAGA with Arbitrary Sampling
Xun Qian · Zheng Qu · Peter Richtarik
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #200
Natural Analysts in Adaptive Data Analysis
Tijana Zrnic · University of California Moritz Hardt
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #201
CapsAndRuns: An Improved Method for Approximately Optimal Algorithm Configuration
Gellért Weisz · Andras Gyorgy · Csaba Szepesvari
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #202
Leveraging Low-Rank Relations Between Surrogate Tasks in Structured Prediction
Giulia Luise · Dimitrios Stamos · Massimiliano Pontil · Carlo Ciliberto
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #203
Training Well-Generalizing Classifiers for Fairness Metrics and Other Data-Dependent Constraints
Andrew Cotter · Maya Gupta · Heinrich Jiang · Nati Srebro · Karthik Sridharan · Serena Wang · Blake Woodworth · Seungil You
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #204
Optimality Implies Kernel Sum Classifiers are Statistically Efficient
Raphael Meyer · Jean Honorio
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #205
The Implicit Fairness Criterion of Unconstrained Learning
Lydia T. Liu · Max Simchowitz · University of California Moritz Hardt
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #206
Weak Detection of Signal in the Spiked Wigner Model
Hye Won Chung · Ji Oon Lee
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #207
Rademacher Complexity for Adversarially Robust Generalization
Dong Yin · Kannan Ramchandran · Peter Bartlett
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #208
Provably efficient RL with Rich Observations via Latent State Decoding
Simon Du · Akshay Krishnamurthy · Nan Jiang · Alekh Agarwal · Miroslav Dudik · John Langford
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #209
Information-Theoretic Considerations in Batch Reinforcement Learning
Jinglin Chen · Nan Jiang
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #210
A Contrastive Divergence for Combining Variational Inference and MCMC
Francisco Ruiz · Michalis Titsias
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #211
Calibrated Approximate Bayesian Inference
Hanwen Xing · Geoff Nicholls · Jeong Lee
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #212
Moment-Based Variational Inference for Markov Jump Processes
Christian Wildner · Heinz Koeppl
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #213
Understanding MCMC Dynamics as Flows on the Wasserstein Space
Chang Liu · Jingwei Zhuo · Jun Zhu
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #214
LR-GLM: High-Dimensional Bayesian Inference Using Low-Rank Data Approximations
Brian Trippe · Jonathan Huggins · Raj Agrawal · Tamara Broderick
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #215
Amortized Monte Carlo Integration
Adam Golinski · Frank Wood · Tom Rainforth
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #216
Stein Point Markov Chain Monte Carlo
Wilson Ye Chen · Alessandro Barp · Francois-Xavier Briol · Jackson Gorham · Mark Girolami · Lester Mackey · Chris Oates
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #217
Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations
Wu Lin · Mohammad Emtiyaz Khan · Mark Schmidt
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #218
Particle Flow Bayes' Rule
Xinshi Chen · Hanjun Dai · Le Song
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #219
Correlated Variational Auto-Encoders
Da Tang · Dawen Liang · Tony Jebara · Nicholas Ruozzi
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #220
Towards a Unified Analysis of Random Fourier Features
Zhu Li · Jean-Francois Ton · Dino Oglic · Dino Sejdinovic
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #221
Learning deep kernels for exponential family densities
Li Kevin Wenliang · Dougal Sutherland · Heiko Strathmann · Arthur Gretton
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #222
Bayesian Deconditional Kernel Mean Embeddings
Kelvin Hsu · Fabio Ramos
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #223
A Kernel Perspective for Regularizing Deep Neural Networks
Alberto Bietti · Gregoire Mialon · Dexiong Chen · Julien Mairal
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #224
A Persistent Weisfeiler--Lehman Procedure for Graph Classification
Bastian Rieck · Christian Bock · Karsten Borgwardt
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #225
Rehashing Kernel Evaluation in High Dimensions
Paris Siminelakis · Kexin Rong · Peter Bailis · Moses Charikar · Philip Levis
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #226
Large-Scale Sparse Kernel Canonical Correlation Analysis
Viivi Uurtio · Sahely Bhadra · Juho Rousu
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #227
A Kernel Theory of Modern Data Augmentation
Tri Dao · Albert Gu · Alexander J Ratner · Virginia Smith · Chris De Sa · Christopher Re
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #228
kernelPSI: a Post-Selection Inference Framework for Nonlinear Variable Selection
Lotfi Slim · Clément Chatelain · Chloe-Agathe Azencott · Jean-Philippe Vert
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #229
Scalable Learning in Reproducing Kernel Krein Spaces
Dino Oglic · Thomas Gaertner
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #230
Dirichlet Simplex Nest and Geometric Inference
Mikhail Yurochkin · Aritra Guha · Yuekai Sun · XuanLong Nguyen
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #231
Bayesian leave-one-out cross-validation for large data
Måns Magnusson · Michael Andersen · Johan Jonasson · Aki Vehtari
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #232
Rao-Blackwellized Stochastic Gradients for Discrete Distributions
Runjing Liu · Jeffrey Regier · Nilesh Tripuraneni · Michael Jordan · Jon McAuliffe
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #233
Neurally-Guided Structure Inference
Sidi Lu · Jiayuan Mao · Josh Tenenbaum · Jiajun Wu
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #234
Bayesian Joint Spike-and-Slab Graphical Lasso
Zehang Li · Tyler Mccormick · Samuel Clark
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #235
Rotation Invariant Householder Parameterization for Bayesian PCA
Rajbir-Singh Nirwan · Nils Bertschinger
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #236
A Framework for Bayesian Optimization in Embedded Subspaces
Amin Nayebi · Alexander Munteanu · Matthias Poloczek
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #237
Convolutional Poisson Gamma Belief Network
CHAOJIE WANG · Bo Chen · SUCHENG XIAO · Mingyuan Zhou
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #238
Automatic Posterior Transformation for Likelihood-Free Inference
David Greenberg · Marcel Nonnenmacher · Jakob Macke
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #239
Active Learning for Decision-Making from Imbalanced Observational Data
Iiris Sundin · Peter Schulam · Eero Siivola · Aki Vehtari · Suchi Saria · Samuel Kaski
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #240
Validating Causal Inference Models via Influence Functions
Ahmed Alaa · M van der Schaar
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #241
Ithemal: Accurate, Portable and Fast Basic Block Throughput Estimation using Deep Neural Networks
Charith Mendis · Alex Renda · Dr.Saman Amarasinghe · Michael Carbin
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #242
Learning to Groove with Inverse Sequence Transformations
Jon Gillick · Adam Roberts · Jesse Engel · Douglas Eck · David Bamman
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #243
Grid-Wise Control for Multi-Agent Reinforcement Learning in Video Game AI
Lei Han · Peng Sun · Yali Du · Jiechao Xiong · Qing Wang · Xinghai Sun · Han Liu · Tong Zhang
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #244
HOList: An Environment for Machine Learning of Higher Order Logic Theorem Proving
Kshitij Bansal · Sarah Loos · Markus Rabe · Christian Szegedy · Stewart Wilcox
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #245
Molecular Hypergraph Grammar with Its Application to Molecular Optimization
Hiroshi Kajino
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #246
Graph Neural Network for Music Score Data and Modeling Expressive Piano Performance
Dasaem Jeong · Taegyun Kwon · Yoojin Kim · Juhan Nam
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom
Learning to Prove Theorems via Interacting with Proof Assistants
Kaiyu Yang · Jia Deng
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #248
Circuit-GNN: Graph Neural Networks for Distributed Circuit Design
GUO ZHANG · Hao He · Dina Katabi
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #249
Learning to Optimize Multigrid PDE Solvers
Daniel Greenfeld · Meirav Galun · Ronen Basri · Irad Yavneh · Ron Kimmel
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #250
A Block Coordinate Descent Proximal Method for Simultaneous Filtering and Parameter Estimation
Ramin Raziperchikolaei · Harish Bhat
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #251
Learning Hawkes Processes Under Synchronization Noise
William Trouleau · Jalal Etesami · Matthias Grossglauser · Negar Kiyavash · Patrick Thiran
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #252
Generative Adversarial User Model for Reinforcement Learning Based Recommendation System
Xinshi Chen · Shuang Li · Hui Li · Shaohua Jiang · Yuan Qi · Le Song
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #253
A Statistical Investigation of Long Memory in Language and Music
Alexander Greaves-Tunnell · Zaid Harchaoui
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #254
Deep Factors for Forecasting
Yuyang Wang · Alex Smola · Danielle Robinson · Jan Gasthaus · Dean Foster · Tim Januschowski
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #255
Weakly-Supervised Temporal Localization via Occurrence Count Learning
Julien Schroeter · Kirill Sidorov · David Marshall
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #256
Switching Linear Dynamics for Variational Bayes Filtering
Philip Becker-Ehmck · Jan Peters · Patrick van der Smagt
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #257
Imputing Missing Events in Continuous-Time Event Streams
Hongyuan Mei · Guanghui Qin · Jason Eisner
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #258
Understanding and Controlling Memory in Recurrent Neural Networks
Doron Haviv · Alexander Rivkind · Omri Barak
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #259
Recurrent Kalman Networks: Factorized Inference in High-Dimensional Deep Feature Spaces
Philipp Becker · Harit Pandya · Gregor Gebhardt · Cheng Zhao · C. James Taylor · Gerhard Neumann
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #260
Subspace Robust Wasserstein Distances
François-Pierre Paty · Marco Cuturi
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #261
Decomposing feature-level variation with Covariate Gaussian Process Latent Variable Models
Kaspar Märtens · Kieran Campbell · Christopher Yau
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #262
Active Manifolds: A non-linear analogue to Active Subspaces
Robert A Bridges · Anthony Gruber · Christopher Felder · Miki Verma · Chelsey Hoff
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #263
Optimal Minimal Margin Maximization with Boosting
Alexander Mathiasen · Kasper Green Larsen · Allan Grønlund
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #264
Generalized Linear Rule Models
Dennis Wei · Sanjeeb Dash · Tian Gao · Oktay Gunluk
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #265
Fast Incremental von Neumann Graph Entropy Computation: Theory, Algorithm, and Applications
Pin-Yu Chen · Lingfei Wu · Sijia Liu · Indika Rajapakse
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #266
Variational Inference for sparse network reconstruction from count data
Julien Chiquet · Stephane Robin · Mahendra Mariadassou
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #267
Simplifying Graph Convolutional Networks
Felix Wu · Amauri Souza · Tianyi Zhang · Christopher Fifty · Tao Yu · Kilian Weinberger
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #268
Robust Influence Maximization for Hyperparametric Models
Dimitrios Kalimeris · Gal Kaplun · Yaron Singer
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #269
HyperGAN: A Generative Model for Diverse, Performant Neural Networks
Neale Ratzlaff · Fuxin Li
Poster
Tue Jun 11th 06:30 -- 06:50 PM @ Pacific Ballroom #270
Rates of Convergence for Sparse Variational Gaussian Process Regression
David Burt · Carl E Rasmussen · Mark van der Wilk
Poster
Tue Jun 11th 06:30 -- 09:00 PM @ Pacific Ballroom #271
Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations
Francesco Locatello · Stefan Bauer · Mario Lucic · Gunnar Raetsch · Sylvain Gelly · Bernhard Schölkopf · Olivier Bachem
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #1
Sum-of-Squares Polynomial Flow
Priyank Jaini · Kira A. Selby · Yaoliang Yu
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #2
FloWaveNet : A Generative Flow for Raw Audio
Sungwon Kim · Sang-gil Lee · Jongyoon Song · Jaehyeon Kim · Sungroh Yoon
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #3
Are Generative Classifiers More Robust to Adversarial Attacks?
Yingzhen Li · John Bradshaw · Yash Sharma
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #4
A Gradual, Semi-Discrete Approach to Generative Network Training via Explicit Wasserstein Minimization
Yucheng Chen · Matus Telgarsky · Chao Zhang · Bolton Bailey · Daniel Hsu · Jian Peng
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #5
Disentangling Disentanglement in Variational Autoencoders
Emile Mathieu · Tom Rainforth · N Siddharth · Yee Whye Teh
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #6
EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE
Chao Ma · Sebastian Tschiatschek · Konstantina Palla · Jose Hernandez-Lobato · Sebastian Nowozin · Cheng Zhang
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #7
A Wrapped Normal Distribution on Hyperbolic Space for Gradient-Based Learning
Yoshihiro Nagano · Shoichiro Yamaguchi · Yasuhiro Fujita · Masanori Koyama
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #8
Emerging Convolutions for Generative Normalizing Flows
Emiel Hoogeboom · Rianne Van den Berg · Max Welling
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #9
A Large-Scale Study on Regularization and Normalization in GANs
Karol Kurach · Mario Lucic · Xiaohua Zhai · Marcin Michalski · Sylvain Gelly
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #10
Variational Annealing of GANs: A Langevin Perspective
Chenyang Tao · Shuyang Dai · Liqun Chen · Ke Bai · Junya Chen · Chang Liu · RUIYI (ROY) ZHANG · Georgiy Bobashev · Lawrence Carin
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #11
Invertible Residual Networks
Jens Behrmann · Will Grathwohl · Tian Qi Chen · David Duvenaud · Joern-Henrik Jacobsen
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #12
NAS-Bench-101: Towards Reproducible Neural Architecture Search
Chris Ying · Aaron Klein · Eric Christiansen · Esteban Real · Kevin Murphy · Frank Hutter
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #13
Approximated Oracle Filter Pruning for Destructive CNN Width Optimization
XIAOHAN DING · guiguang ding · Yuchen Guo · Jungong Han · Chenggang Yan
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #14
LegoNet: Efficient Convolutional Neural Networks with Lego Filters
Zhaohui Yang · Yunhe Wang · Chuanjian Liu · Hanting Chen · Chunjing Xu · Boxin Shi · Chao Xu · Chang Xu
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #15
Sorting Out Lipschitz Function Approximation
Cem Anil · James Lucas · Roger Grosse
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #16
Graph Element Networks: adaptive, structured computation and memory
Ferran Alet · Adarsh Keshav Jeewajee · Maria Bauza Villalonga · Alberto Rodriguez · Tomas Lozano-Perez · Leslie Kaelbling
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #17
Training CNNs with Selective Allocation of Channels
Jongheon Jeong · Jinwoo Shin
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #18
Equivariant Transformer Networks
Kai Sheng Tai · Peter Bailis · Gregory Valiant
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #19
Overcoming Multi-model Forgetting
Yassine Benyahia · Kaicheng Yu · Kamil Bennani-Smires · Martin Jaggi · Anthony C. Davison · Mathieu Salzmann · Claudiu Musat
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #20
Bayesian Nonparametric Federated Learning of Neural Networks
Mikhail Yurochkin · Mayank Agarwal · Soumya Ghosh · Kristjan Greenewald · Nghia Hoang · Yasaman Khazaeni
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #21
How does Disagreement Help Generalization against Label Corruption?
Xingrui Yu · Bo Han · Jiangchao Yao · Gang Niu · Ivor Tsang · Masashi Sugiyama
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #22
EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis
Chaoqi Wang · Roger Grosse · Sanja Fidler · Guodong Zhang
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #23
Addressing the Loss-Metric Mismatch with Adaptive Loss Alignment
Chen Huang · Shuangfei Zhai · Walter Talbott · Miguel Bautista Martin · Shih-Yu Sun · Carlos Guestrin · Joshua M Susskind
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #24
Deep Compressed Sensing
Yan Wu · Mihaela Rosca · Timothy Lillicrap
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #25
Differentiable Dynamic Normalization for Learning Deep Representation
Ping Luo · Peng Zhanglin · Shao Wenqi · Zhang ruimao · Ren jiamin · Wu lingyun
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #26
Toward Understanding the Importance of Noise in Training Neural Networks
Mo Zhou · Tianyi Liu · Yan Li · Dachao Lin · Enlu Zhou · Tuo Zhao
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #27
Cheap Orthogonal Constraints in Neural Networks: A Simple Parametrization of the Orthogonal and Unitary Group
Mario Lezcano Casado · David Martínez-Rubio
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #28
Breaking Inter-Layer Co-Adaptation by Classifier Anonymization
Ikuro Sato · Kohta Ishikawa · Guoqing Liu · Masayuki Tanaka
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #29
Understanding the Impact of Entropy on Policy Optimization
Zafarali Ahmed · Nicolas Le Roux · Mohammad Norouzi · Dale Schuurmans
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #30
Probability Functional Descent: A Unifying Perspective on GANs, Variational Inference, and Reinforcement Learning
Casey Chu · Jose Blanchet · Peter Glynn
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #31
Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning
Natasha Jaques · Angeliki Lazaridou · Edward Hughes · Caglar Gulcehre · Pedro Ortega · DJ Strouse · Joel Z Leibo · Nando de Freitas
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #32
Maximum Entropy-Regularized Multi-Goal Reinforcement Learning
Rui Zhao · Xudong Sun · Volker Tresp
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #33
Imitating Latent Policies from Observation
Ashley Edwards · Himanshu Sahni · Yannick Schroecker · Charles Isbell
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #34
SOLAR: Deep Structured Representations for Model-Based Reinforcement Learning
Marvin Zhang · Sharad Vikram · Laura Smith · Pieter Abbeel · Matthew Johnson · Sergey Levine
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #35
Dimension-Wise Importance Sampling Weight Clipping for Sample-Efficient Reinforcement Learning
Seungyul Han · Youngchul Sung
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #36
Structured agents for physical construction
Victor Bapst · Alvaro Sanchez · Carl Doersch · Kimberly Stachenfeld · Pushmeet Kohli · Peter Battaglia · Jessica Hamrick
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #37
Learning Novel Policies For Tasks
Yunbo Zhang · Wenhao Yu · Greg Turk
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #38
Taming MAML: Efficient unbiased meta-reinforcement learning
Hao Liu · Richard Socher · Caiming Xiong
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #39
Self-Supervised Exploration via Disagreement
Deepak Pathak · Dhiraj Gandhi · Abhinav Gupta
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #40
Efficient Off-Policy Meta-Reinforcement Learning via Probabilistic Context Variables
Kate Rakelly · Aurick Zhou · Chelsea Finn · Sergey Levine · Deirdre Quillen
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #41
The Natural Language of Actions
Guy Tennenholtz · Shie Mannor
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #42
Control Regularization for Reduced Variance Reinforcement Learning
Richard Cheng · Abhinav Verma · Gabor Orosz · Swarat Chaudhuri · Yisong Yue · Joel Burdick
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #43
On the Generalization Gap in Reparameterizable Reinforcement Learning
Huan Wang · Stephan Zheng · Caiming Xiong · Richard Socher
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #44
Trajectory-Based Off-Policy Deep Reinforcement Learning
Andreas Doerr · Michael Volpp · Marc Toussaint · Sebastian Trimpe · Christian Daniel
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #45
A Deep Reinforcement Learning Perspective on Internet Congestion Control
Nathan Jay · Noga H. Rotman · Brighten Godfrey · Michael Schapira · Aviv Tamar
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #46
Model-Based Active Exploration
Pranav Shyam · Wojciech Jaśkowski · Faustino Gomez
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #47
Extrapolating Beyond Suboptimal Demonstrations via Inverse Reinforcement Learning from Observations
Daniel Brown · Wonjoon Goo · Prabhat Nagarajan · Scott Niekum
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #48
Distributional Multivariate Policy Evaluation and Exploration with the Bellman GAN
dror freirich · Tzahi Shimkin · Ron Meir · Aviv Tamar
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #49
A Baseline for Any Order Gradient Estimation in Stochastic Computation Graphs
Jingkai Mao · Jakob Foerster · Tim Rocktäschel · Maruan Al-Shedivat · Gregory Farquhar · Shimon Whiteson
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #50
Remember and Forget for Experience Replay
Guido Novati · Petros Koumoutsakos
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #51
Tensor Variable Elimination for Plated Factor Graphs
Fritz Obermeyer · Elias Bingham · Martin Jankowiak · Neeraj Pradhan · Justin Chiu · Alexander Rush · Noah Goodman
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #52
Predicate Exchange: Inference with Declarative Knowledge
Zenna Tavares · Javier Burroni · Edgar Minasyan · Armando Solar-Lezama · Rajesh Ranganath
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #53
Discriminative Regularization for Latent Variable Models with Applications to Electrocardiography
Andrew Miller · Ziad Obermeyer · John Cunningham · Sendhil Mullainathan
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #54
Hierarchical Decompositional Mixtures of Variational Autoencoders
Ping Liang Tan · Robert Peharz
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #55
Finding Mixed Nash Equilibria of Generative Adversarial Networks
Ya-Ping Hsieh · Chen Liu · Volkan Cevher
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #56
CompILE: Compositional Imitation Learning and Execution
Thomas Kipf · Yujia Li · Hanjun Dai · Vinicius Zambaldi · Alvaro Sanchez · Edward Grefenstette · Pushmeet Kohli · Peter Battaglia
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #57
Sparse Multi-Channel Variational Autoencoder for the Joint Analysis of Heterogeneous Data
Luigi Antelmi · Nicholas Ayache · Philippe Robert · Marco Lorenzi
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #58
Deep Generative Learning via Variational Gradient Flow
Yuan Gao · Yuling Jiao · Yang Wang · Yao Wang · Can Yang · Shunkang Zhang
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #59
Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design
Jonathan Ho · Peter Chen · Aravind Srinivas · Rocky Duan · Pieter Abbeel
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #60
Learning Neurosymbolic Generative Models via Program Synthesis
Halley R Young · Osbert Bastani · Mayur Naik
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #61
Theoretically Principled Trade-off between Robustness and Accuracy
Hongyang Zhang · Yaodong Yu · Jiantao Jiao · Eric Xing · Laurent El Ghaoui · Michael Jordan
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #62
The Odds are Odd: A Statistical Test for Detecting Adversarial Examples
Kevin Roth · Yannic Kilcher · Thomas Hofmann
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #63
ME-Net: Towards Effective Adversarial Robustness with Matrix Estimation
Yuzhe Yang · GUO ZHANG · Zhi Xu · Dina Katabi
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #64
Certified Adversarial Robustness via Randomized Smoothing
Jeremy Cohen · Elan Rosenfeld · Zico Kolter
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #65
Imperceptible, Robust, and Targeted Adversarial Examples for Automatic Speech Recognition
Yao Qin · Nicholas Carlini · Garrison Cottrell · Ian Goodfellow · Colin Raffel
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #66
Parsimonious Black-Box Adversarial Attacks via Efficient Combinatorial Optimization
Seungyong Moon · Gaon An · Hyun Oh Song
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #67
Wasserstein Adversarial Examples via Projected Sinkhorn Iterations
Eric Wong · Frank Schmidt · Zico Kolter
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #68
Transferable Clean-Label Poisoning Attacks on Deep Neural Nets
Chen Zhu · Ronny Huang · Hengduo Li · Gavin Taylor · Christoph Studer · Tom Goldstein
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #69
NATTACK: Learning the Distributions of Adversarial Examples for an Improved Black-Box Attack on Deep Neural Networks
Yandong li · Lijun Li · Liqiang Wang · Tong Zhang · Boqing Gong
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #70
Simple Black-box Adversarial Attacks
Chuan Guo · Jacob Gardner · Yurong You · Andrew Wilson · Kilian Weinberger
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #71
Causal Identification under Markov Equivalence: Completeness Results
Amin Jaber · Jiji Zhang · Elias Bareinboim
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #72
Counterfactual Off-Policy Evaluation with Gumbel-Max Structural Causal Models
Michael Oberst · David Sontag
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #73
Causal Discovery and Forecasting in Nonstationary Environments with State-Space Models
Biwei Huang · Kun Zhang · Mingming Gong · Clark Glymour
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #74
Classifying Treatment Responders Under Causal Effect Monotonicity
Nathan Kallus
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #75
Learning Models from Data with Measurement Error: Tackling Underreporting
Roy Adams · Yuelong Ji · Xiaobin Wang · Suchi Saria
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #76
Adjustment Criteria for Generalizing Experimental Findings
Juan Correa · Jin Tian · Elias Bareinboim
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #77
Conditional Independence in Testing Bayesian Networks
Yujia Shen · Haiying Huang · Arthur Choi · Adnan Darwiche
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #78
Sensitivity Analysis of Linear Structural Causal Models
Carlos Cinelli · Daniel Kumor · Bryant Chen · Judea Pearl · Elias Bareinboim
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #79
More Efficient Off-Policy Evaluation through Regularized Targeted Learning
Aurelien Bibaut · Ivana Malenica · Nikos Vlassis · Mark van der Laan
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #80
Inferring Heterogeneous Causal Effects in Presence of Spatial Confounding
Muhammad Osama · Dave Zachariah · Thomas Schön
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #81
Adversarially Learned Representations for Information Obfuscation and Inference
Martin A Bertran · Natalia Martinez · Afroditi Papadaki · Qiang Qiu · Miguel Rodrigues · Galen Reeves · Guillermo Sapiro
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #82
Adaptive Neural Trees
Ryutaro Tanno · Kai Arulkumaran · Daniel Alexander · Antonio Criminisi · Aditya Nori
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #83
Connectivity-Optimized Representation Learning via Persistent Homology
Christoph Hofer · Roland Kwitt · Marc Niethammer · Mandar Dixit
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #84
Minimal Achievable Sufficient Statistic Learning
Milan Cvitkovic · Günther Koliander
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #85
Learning to Route in Similarity Graphs
Dmitry Baranchuk · Dmitry Persiyanov · Anton Sinitsin · Artem Babenko
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #86
Invariant-Equivariant Representation Learning for Multi-Class Data
Ilya Feige
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #87
Infinite Mixture Prototypes for Few-shot Learning
Kelsey Allen · Evan Shelhamer · Hanul Shin · Josh Tenenbaum
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #88
MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing
Sami Abu-El-Haija · Bryan Perozzi · Amol Kapoor · Nazanin Alipourfard · Kristina Lerman · Hrayr Harutyunyan · Greg Ver Steeg · Aram Galstyan
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #89
Learn to Grow: A Continual Structure Learning Framework for Overcoming Catastrophic Forgetting
Xilai Li · Yingbo Zhou · Tianfu Wu · Richard Socher · Caiming Xiong
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #90
Exploration Conscious Reinforcement Learning Revisited
Lior Shani · Yonathan Efroni · Shie Mannor
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #91
Complexity of Linear Regions in Deep Networks
Boris Hanin · David Rolnick
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #92
On Connected Sublevel Sets in Deep Learning
Quynh Nguyen
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #93
Adversarial Examples Are a Natural Consequence of Test Error in Noise
Justin Gilmer · Nicolas Ford · Nicholas Carlini · Ekin Cubuk
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #94
Greedy Layerwise Learning Can Scale To ImageNet
Eugene Belilovsky · Michael Eickenberg · Edouard Oyallon
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #95
On the Impact of the Activation function on Deep Neural Networks Training
Soufiane Hayou · Arnaud Doucet · Judith Rousseau
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #96
Estimating Information Flow in Deep Neural Networks
Ziv Goldfeld · Ewout van den Berg · Kristjan Greenewald · Igor Melnyk · Nam Nguyen · Brian Kingsbury · Yury Polyanskiy
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #97
The Anisotropic Noise in Stochastic Gradient Descent: Its Behavior of Escaping from Sharp Minima and Regularization Effects
Zhanxing Zhu · Jingfeng Wu · Bing Yu · Lei Wu · Jinwen Ma
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #98
Characterizing Well-Behaved vs. Pathological Deep Neural Networks
Antoine Labatie
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #99
Understanding Geometry of Encoder-Decoder CNNs
Jong Chul Ye · woonkyoung Sung
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #100
Traditional and Heavy Tailed Self Regularization in Neural Network Models
Michael Mahoney · Charles H Martin
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #101
Almost surely constrained convex optimization
Olivier Fercoq · Ahmet Alacaoglu · Ion Necoara · Volkan Cevher
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #102
Generalized Majorization-Minimization
Sobhan Naderi Parizi · Kun He · Reza Aghajani · Stan Sclaroff · Pedro Felzenszwalb
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #103
On the Computation and Communication Complexity of Parallel SGD with Dynamic Batch Sizes for Stochastic Non-Convex Optimization
Hao Yu · rong jin
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #104
Simple Stochastic Gradient Methods for Non-Smooth Non-Convex Regularized Optimization
Michael Metel · Akiko Takeda
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #105
Surrogate Losses for Online Learning of Stepsizes in Stochastic Non-Convex Optimization
zhenxun zhuang · Ashok Cutkosky · Francesco Orabona
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #106
Efficient Dictionary Learning with Gradient Descent
Dar Gilboa · Sam Buchanan · John Wright
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #107
Plug-and-Play Methods Provably Converge with Properly Trained Denoisers
Ernest Ryu · Jialin Liu · Sicheng Wang · Xiaohan Chen · Zhangyang Wang · Wotao Yin
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #108
Riemannian adaptive stochastic gradient algorithms on matrix manifolds
Hiroyuki Kasai · Pratik Kumar Jawanpuria · Bamdev Mishra
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #109
Stochastic Optimization for DC Functions and Non-smooth Non-convex Regularizers with Non-asymptotic Convergence
Yi Xu · Qi Qi · Qihang Lin · rong jin · Tianbao Yang
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #110
Alternating Minimizations Converge to Second-Order Optimal Solutions
Qiuwei Li · Zhihui Zhu · Gongguo Tang
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #111
Provably Efficient Imitation Learning from Observation Alone
Wen Sun · Anirudh Vemula · Byron Boots · Drew Bagnell
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #112
Dead-ends and Secure Exploration in Reinforcement Learning
Mehdi Fatemi · Shikhar Sharma · Harm van Seijen · Samira Ebrahimi Kahou
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #113
Statistics and Samples in Distributional Reinforcement Learning
Mark Rowland · Robert Dadashi · Saurabh Kumar · Remi Munos · Marc Bellemare · Will Dabney
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #114
Hessian Aided Policy Gradient
Zebang Shen · Alejandro Ribeiro · Hamed Hassani · Hui Qian · Chao Mi
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #115
Provably Efficient Maximum Entropy Exploration
Elad Hazan · Sham Kakade · Karan Singh · Abby Van Soest
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #116
Combining parametric and nonparametric models for off-policy evaluation
Omer Gottesman · Yao Liu · Scott Sussex · Emma Brunskill · Finale Doshi-Velez
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #117
Sample-Optimal Parametric Q-Learning Using Linearly Additive Features
Lin Yang · Mengdi Wang
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #118
Transfer of Samples in Policy Search via Multiple Importance Sampling
Andrea Tirinzoni · Mattia Salvini · Marcello Restelli
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #119
Action Robust Reinforcement Learning and Applications in Continuous Control
Chen Tessler · Yonathan Efroni · Shie Mannor
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #120
Kernel-Based Reinforcement Learning in Robust Markov Decision Processes
Shiau Hong Lim · Arnaud Autef
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #121
Optimal Algorithms for Lipschitz Bandits with Heavy-tailed Rewards
Shiyin Lu · Guanghui Wang · Yao Hu · Lijun Zhang
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #122
Target Tracking for Contextual Bandits: Application to Demand Side Management
Margaux Brégère · Pierre Gaillard · Yannig Goude · Gilles Stoltz
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #123
Correlated bandits or: How to minimize mean-squared error online
Vinay Praneeth Boda · Prashanth L.A.
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #124
Stay With Me: Lifetime Maximization Through Heteroscedastic Linear Bandits With Reneging
Ping-Chun Hsieh · Xi Liu · Anirban Bhattacharya · P R Kumar
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #125
Garbage In, Reward Out: Bootstrapping Exploration in Multi-Armed Bandits
Branislav Kveton · Csaba Szepesvari · Sharan Vaswani · Zheng Wen · Tor Lattimore · Mohammad Ghavamzadeh
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #126
Beating Stochastic and Adversarial Semi-bandits Optimally and Simultaneously
Julian Zimmert · Haipeng Luo · Chen-Yu Wei
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #127
Bilinear Bandits with Low-rank Structure
Kwang-Sung Jun · Rebecca Willett · Stephen Wright · Robert Nowak
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #128
Online Learning to Rank with Features
Shuai Li · Tor Lattimore · Csaba Szepesvari
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #129
On the Design of Estimators for Bandit Off-Policy Evaluation
Nikos Vlassis · Aurelien Bibaut · Maria Dimakopoulou · Tony Jebara
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #130
Dynamic Learning with Frequent New Product Launches: A Sequential Multinomial Logit Bandit Problem
Junyu Cao · Wei Sun
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #131
Context-Aware Zero-Shot Learning for Object Recognition
Eloi Zablocki · Patrick Bordes · Laure Soulier · Benjamin Piwowarski · Patrick Gallinari
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #132
Band-limited Training and Inference for Convolutional Neural Networks
Adam Dziedzic · John Paparrizos · Sanjay Krishnan · Aaron Elmore · Michael Franklin
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #133
Learning Classifiers for Target Domain with Limited or No Labels
Pengkai Zhu · Hanxiao Wang · Venkatesh Saligrama
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #134
Population Based Augmentation: Efficient Learning of Augmentation Policy Schedules
Daniel Ho · Eric Liang · Peter Chen · Ion Stoica · Pieter Abbeel
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #135
Anomaly Detection With Multiple-Hypotheses Predictions
Duc Tam Nguyen · Zhongyu Lou · Michael Klar · Thomas Brox
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #136
Kernel Mean Matching for Content Addressability of GANs
Wittawat Jitkrittum · Patsorn Sangkloy · Muhammad Waleed Gondal · Amit Raj · James Hays · Bernhard Schölkopf
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #137
Neural Inverse Knitting: From Images to Manufacturing Instructions
Alexandre Kaspar · Tae-Hyun Oh · Liane Makatura · Petr Kellnhofer · Wojciech Matusik
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #138
Making Convolutional Networks Shift-Invariant Again
Richard Zhang
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #139
Generative Modeling of Infinite Occluded Objects for Compositional Scene Representation
Jinyang Yuan · Bin Li · Xiangyang Xue
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #140
IMEXnet - A Forward Stable Deep Neural Network
Eldad Haber · Keegan Lensink · Eran Treister · Lars Ruthotto
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #141
Do ImageNet Classifiers Generalize to ImageNet?
Benjamin Recht · Rebecca Roelofs · Ludwig Schmidt · Vaishaal Shankar
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #142
Exploring the Landscape of Spatial Robustness
Logan Engstrom · Brandon Tran · Dimitris Tsipras · Ludwig Schmidt · Aleksander Madry
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #143
Sever: A Robust Meta-Algorithm for Stochastic Optimization
Ilias Diakonikolas · Gautam Kamath · Daniel Kane · Jerry Li · Jacob Steinhardt · Alistair Stewart
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #144
Analyzing Federated Learning through an Adversarial Lens
Arjun Nitin Bhagoji · Supriyo Chakraborty · Prateek Mittal · Seraphin Calo
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #145
Fairwashing: the risk of rationalization
Ulrich AIVODJI · Hiromi Arai · Olivier Fortineau · Sébastien Gambs · Satoshi Hara · Alain Tapp
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #146
Understanding the Origins of Bias in Word Embeddings
Marc-Etienne Brunet · Colleen Alkalay-Houlihan · Ashton Anderson · Richard Zemel
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #147
Bias Also Matters: Bias Attribution for Deep Neural Network Explanation
Shengjie Wang · Tianyi Zhou · Jeff Bilmes
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #148
Interpreting Adversarially Trained Convolutional Neural Networks
Tianyuan Zhang · Zhanxing Zhu
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #149
Counterfactual Visual Explanations
Yash Goyal · Ziyan Wu · Jan Ernst · Dhruv Batra · Devi Parikh · Stefan Lee
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #150
Data Poisoning Attacks on Stochastic Bandits
Fang Liu · Ness Shroff
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #151
On the Convergence and Robustness of Adversarial Training
Yisen Wang · Xingjun Ma · James Bailey · Jinfeng Yi · Bowen Zhou · Quanquan Gu
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #152
Learning with Bad Training Data via Iterative Trimmed Loss Minimization
Yanyao Shen · Sujay Sanghavi
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #153
On discriminative learning of prediction uncertainty
Vojtech Franc · Daniel Prusa
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #154
Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels
Pengfei Chen · Ben Ben Liao · Guangyong Chen · Shengyu Zhang
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #155
Does Data Augmentation Lead to Positive Margin?
Shashank Rajput · Zhili Feng · Zachary Charles · Po-Ling Loh · Dimitris Papailiopoulos
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #156
Robust Learning from Untrusted Sources
Nikola Konstantinov · Christoph H. Lampert
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #157
SELFIE: Refurbishing Unclean Samples for Robust Deep Learning
Hwanjun Song · Minseok Kim · Jae-Gil Lee
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #158
Zeno: Distributed Stochastic Gradient Descent with Suspicion-based Fault-tolerance
Cong Xie · Sanmi Koyejo · Indranil Gupta
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #159
Concentration Inequalities for Conditional Value at Risk
Philip Thomas · Erik Learned-Miller
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #160
Data Poisoning Attacks in Multi-Party Learning
Saeed Mahloujifar · Mohammad Mahmoody · Ameer Mohammed
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #161
Distributed Weighted Matching via Randomized Composable Coresets
Sepehr Assadi · Mohammad Hossein Bateni · Vahab Mirrokni
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #162
Multivariate Submodular Optimization
Richard Santiago · F. Bruce Shepherd
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #163
Beyond Adaptive Submodularity: Approximation Guarantees of Greedy Policy with Adaptive Submodularity Ratio
Kaito Fujii · Shinsaku Sakaue
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #164
Approximating Orthogonal Matrices with Effective Givens Factorization
Thomas Frerix · Joan Bruna
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #165
New results on information theoretic clustering
Ferdinando Cicalese · Eduardo Laber · Lucas Murtinho
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #166
Improved Parallel Algorithms for Density-Based Network Clustering
Mohsen Ghaffari · Silvio Lattanzi · Slobodan Mitrović
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #167
Submodular Observation Selection and Information Gathering for Quadratic Models
Abolfazl Hashemi · Mahsa Ghasemi · Haris Vikalo · Ufuk Topcu
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #168
Submodular Cost Submodular Cover with an Approximate Oracle
Victoria Crawford · Alan Kuhnle · My T Thai
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #169
Submodular Streaming in All Its Glory: Tight Approximation, Minimum Memory and Low Adaptive Complexity
Ehsan Kazemi · Marko Mitrovic · Morteza Zadimoghaddam · Silvio Lattanzi · Amin Karbasi
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #170
Hiring Under Uncertainty
Manish Purohit · Sreenivas Gollapudi · Manish Raghavan
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #171
Position-aware Graph Neural Networks
Jiaxuan You · Rex (Zhitao) Ying · Jure Leskovec
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #172
Detecting Overlapping and Correlated Communities without Pure Nodes: Identifiability and Algorithm
Kejun Huang · Xiao Fu
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #173
Learning Generative Models across Incomparable Spaces
Charlotte Bunne · David Alvarez-Melis · Andreas Krause · Stefanie Jegelka
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #174
Relational Pooling for Graph Representations
Ryan Murphy · Balasubramaniam Srinivasan · Vinayak A Rao · Bruno Ribeiro
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #175
Disentangled Graph Convolutional Networks
Jianxin Ma · Peng Cui · Kun Kuang · Xin Wang · wenwu zhu
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #176
Open Vocabulary Learning on Source Code with a Graph-Structured Cache
Milan Cvitkovic · Badal Singh · Anima Anandkumar
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #177
Learning Discrete Structures for Graph Neural Networks
Luca Franceschi · Mathias Niepert · Massimiliano Pontil · Xiao He
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #178
Compositional Fairness Constraints for Graph Embeddings
Avishek Bose · William Hamilton
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #179
A Recurrent Neural Cascade-based Model for Continuous-Time Diffusion
Sylvain Lamprier
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #180
Stochastic Blockmodels meet Graph Neural Networks
Nikhil Mehta · Lawrence Carin · Piyush Rai
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #181
Distributed Learning with Sublinear Communication
Jayadev Acharya · Chris De Sa · Dylan Foster · Karthik Sridharan
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #182
On the Linear Speedup Analysis of Communication Efficient Momentum SGD for Distributed Non-Convex Optimization
Hao Yu · rong jin · Sen Yang
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #183
Stochastic Gradient Push for Distributed Deep Learning
Mahmoud Assran · Nicolas Loizou · Nicolas Ballas · Michael Rabbat
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #184
Collective Model Fusion for Multiple Black-Box Experts
Minh Hoang · Nghia Hoang · Bryan Kian Hsiang Low · Carleton Kingsford
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #185
Trading Redundancy for Communication: Speeding up Distributed SGD for Non-convex Optimization
Farzin Haddadpour · Mohammad Mahdi Kamani · Mehrdad Mahdavi · Viveck Cadambe
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #186
Trimming the $\ell_1$ Regularizer: Statistical Analysis, Optimization, and Applications to Deep Learning
Jihun Yun · Peng Zheng · Eunho Yang · Aurelie Lozano · Aleksandr Aravkin
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #187
Compressed Factorization: Fast and Accurate Low-Rank Factorization of Compressively-Sensed Data
Vatsal Sharan · Kai Sheng Tai · Peter Bailis · Gregory Valiant
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #188
Noisy Dual Principal Component Pursuit
Tianyu Ding · Zhihui Zhu · Tianjiao Ding · Yunchen Yang · Daniel Robinson · Manolis Tsakiris · Rene Vidal
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #189
Learning a Compressed Sensing Measurement Matrix via Gradient Unrolling
Shanshan Wu · Alexandros Dimakis · Sujay Sanghavi · Felix Xinnan Yu · Daniel Holtmann-Rice · Dmitry Storcheus · Afshin Rostamizadeh · Sanjiv Kumar
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #190
Screening rules for Lasso with non-convex Sparse Regularizers
alain rakotomamonjy · Gilles Gasso · Joseph Salmon
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #191
Monge blunts Bayes: Hardness Results for Adversarial Training
Zac Cranko · Aditya Menon · Richard Nock · Cheng Soon Ong · Zhan Shi · Christian Walder
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #192
Better generalization with less data using robust gradient descent
Matthew Holland · Kazushi Ikeda
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #193
Near optimal finite time identification of arbitrary linear dynamical systems
Tuhin Sarkar · Alexander Rakhlin
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #194
Lossless or Quantized Boosting with Integer Arithmetic
Richard Nock · Robert C Williamson
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #195
Orthogonal Random Forest for Causal Inference
Miruna Oprescu · Vasilis Syrgkanis · Zhiwei Steven Wu
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #196
MONK -- Outlier-Robust Mean Embedding Estimation by Median-of-Means
Matthieu Lerasle · Zoltan Szabo · Timothée Mathieu · Guillaume Lecue
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #197
The advantages of multiple classes for reducing overfitting from test set reuse
Vitaly Feldman · Roy Frostig · Moritz Hardt
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #198
On the statistical rate of nonlinear recovery in generative models with heavy-tailed data
Xiaohan Wei · Zhuoran Yang · Zhaoran Wang
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #199
Phase transition in PCA with missing data: Reduced signal-to-noise ratio, not sample size!
Niels Ipsen · Lars Kai Hansen
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #200
On Medians of (Randomized) Pairwise Means
Stephan Clemencon · Pierre Laforgue · Patrice Bertail
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #201
Accelerated Linear Convergence of Stochastic Momentum Methods in Wasserstein Distances
Bugra Can · Mert Gurbuzbalaban · Lingjiong Zhu
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #202
SGD without Replacement: Sharper Rates for General Smooth Convex Functions
Dheeraj Nagaraj · Prateek Jain · Praneeth Netrapalli
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #203
On the Complexity of Approximating Wasserstein Barycenters
Alexey Kroshnin · Nazarii Tupitsa · Darina Dvinskikh · Pavel Dvurechenskii · Alexander Gasnikov · Cesar Uribe
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #204
Estimate Sequences for Variance-Reduced Stochastic Composite Optimization
Andrei Kulunchakov · Julien Mairal
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #205
A Dynamical Systems Perspective on Nesterov Acceleration
Michael Muehlebach · Michael Jordan
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #206
Random Shuffling Beats SGD after Finite Epochs
Jeff HaoChen · Suvrit Sra
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #207
First-Order Algorithms Converge Faster than $O(1/k)$ on Convex Problems
Ching-pei Lee · Stephen Wright
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #208
Improved Convergence for $\ell_1$ and $\ell_\infty$ Regression via Iteratively Reweighted Least Squares
Alina Ene · Adrian Vladu
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #209
Optimal Mini-Batch and Step Sizes for SAGA
Nidham Gazagnadou · Robert Gower · Joseph Salmon
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #210
Differential Inclusions for Modeling Nonsmooth ADMM Variants: A Continuous Limit Theory
Huizhuo Yuan · Yuren Zhou · Chris Junchi Li · Qingyun Sun
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #211
Distribution calibration for regression
Hao Song · Tom Diethe · Meelis Kull · Peter Flach
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #212
Graph Convolutional Gaussian Processes
Ian Walker · Ben Glocker
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #213
Asynchronous Batch Bayesian Optimisation with Improved Local Penalisation
Ahsan Alvi · Binxin Ru · Jan-Peter Calliess · Stephen Roberts · Michael A Osborne
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #214
GOODE: A Gaussian Off-The-Shelf Ordinary Differential Equation Solver
David John · Vincent Heuveline · Michael Schober
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #215
Overcoming Mean-Field Approximations in Recurrent Gaussian Process Models
Alessandro Davide Ialongo · Mark van der Wilk · James Hensman · Carl E Rasmussen
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #216
AReS and MaRS - Adversarial and MMD-Minimizing Regression for SDEs
Gabriele Abbati · Philippe Wenk · Michael A Osborne · Andreas Krause · Bernhard Schölkopf · Stefan Bauer
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #217
End-to-End Probabilistic Inference for Nonstationary Audio Analysis
William Wilkinson · Michael Riis Andersen · Joshua D. Reiss · Dan Stowell · Arno Solin
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #218
Deep Gaussian Processes with Importance-Weighted Variational Inference
Hugh Salimbeni · Vincent Dutordoir · James Hensman · Marc P Deisenroth
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #219
Automated Model Selection with Bayesian Quadrature
Henry Chai · Jean-Francois Ton · Michael A Osborne · Roman Garnett
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #220
Beyond the Chinese Restaurant and Pitman-Yor processes: Statistical Models with double power-law behavior
Fadhel Ayed · Juho Lee · Francois Caron
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #221
DP-GP-LVM: A Bayesian Non-Parametric Model for Learning Multivariate Dependency Structures
Andrew R Lawrence · Carl Henrik Ek · Neill Campbell
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #222
Random Function Priors for Correlation Modeling
Aonan Zhang · John Paisley
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #223
Variational Russian Roulette for Deep Bayesian Nonparametrics
Kai Xu · Akash Srivastava · Charles Sutton
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #224
Incorporating Grouping Information into Bayesian Decision Tree Ensembles
JUNLIANG DU · Antonio Linero
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #225
Variational Implicit Processes
Chao Ma · Yingzhen Li · Jose Hernandez-Lobato
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #226
Discovering Latent Covariance Structures for Multiple Time Series
Anh Tong · Jaesik Choi
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #227
Scalable Training of Inference Networks for Gaussian-Process Models
Jiaxin Shi · Mohammad Emtiyaz Khan · Jun Zhu
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #228
Bayesian Optimization Meets Bayesian Optimal Stopping
Zhongxiang Dai · Haibin Yu · Bryan Kian Hsiang Low · Patrick Jaillet
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #229
Learning interpretable continuous-time models of latent stochastic dynamical systems
Lea Duncker · Gergo Bohner · Julien Boussard · Maneesh Sahani
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #230
A Tree-Based Method for Fast Repeated Sampling of Determinantal Point Processes
Jennifer Gillenwater · Alex Kulesza · Zelda Mariet · Sergei Vassilvitskii
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #231
Nonlinear Stein Variational Gradient Descent for Learning Diversified Mixture Models
Dilin Wang · Qiang Liu
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #232
Understanding and Accelerating Particle-Based Variational Inference
Chang Liu · Jingwei Zhuo · Pengyu Cheng · RUIYI (ROY) ZHANG · Jun Zhu
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #233
Efficient learning of smooth probability functions from Bernoulli tests with guarantees
Paul Rolland · Ali Kavis · Alexander Niklaus Immer · Adish Singla · Volkan Cevher
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #234
The Variational Predictive Natural Gradient
Da Tang · Rajesh Ranganath
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #235
Scalable Nonparametric Sampling from Multimodal Posteriors with the Posterior Bootstrap
Edwin Fong · Simon Lyddon · Christopher Holmes
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #236
An Instability in Variational Inference for Topic Models
Behrooz Ghorbani · Hamidreza Hakim Javadi · Andrea Montanari
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #237
Bayesian Optimization of Composite Functions
Raul Astudillo · Peter Frazier
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #238
The Kernel Interaction Trick: Fast Bayesian Discovery of Pairwise Interactions in High Dimensions
Raj Agrawal · Brian Trippe · Jonathan Huggins · Tamara Broderick
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #239
Quantile Stein Variational Gradient Descent for Batch Bayesian Optimization
Chengyue Gong · Jian Peng · Qiang Liu
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #240
Exploiting Worker Correlation for Label Aggregation in Crowdsourcing
Yuan Li · Benjamin Rubinstein · Trevor Cohn
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #241
Efficient Amortised Bayesian Inference for Hierarchical and Nonlinear Dynamical Systems
Ted Meeds · Geoffrey Roeder · Paul Grant · Andrew Phillips · Neil Dalchau
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #242
A Multitask Multiple Kernel Learning Algorithm for Survival Analysis with Application to Cancer Biology
Onur Dereli · Ceyda Oğuz · Mehmet Gönen
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #243
Fast and Flexible Inference of Joint Distributions from their Marginals
Charles Frogner · Tomaso Poggio
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #244
Cognitive model priors for predicting human decisions
Joshua C Peterson · David D Bourgin · Daniel Reichman · Thomas Griffiths · Stuart Russell
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom
Conditioning by adaptive sampling for robust design
David Brookes · Jennifer Listgarten
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #246
Direct Uncertainty Prediction for Medical Second Opinions
Maithra Raghu · Katy Blumer · Rory sayres · Ziad Obermeyer · Bobby Kleinberg · Sendhil Mullainathan · Jon Kleinberg
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #247
Dynamic Measurement Scheduling for Event Forecasting using Deep RL
Chun-Hao Chang · Mingjie Mai · Anna Goldenberg
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #248
Parameter efficient training of deep convolutional neural networks by dynamic sparse reparameterization
Hesham Mostafa · Xin Wang
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #249
DeepNose: Using artificial neural networks to represent the space of odorants
Ngoc Tran · Daniel Kepple · Sergey Shuvaev · Alexei Koulakov
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #250
Domain Agnostic Learning with Disentangled Representations
Xingchao Peng · Zijun Huang · Ximeng Sun · Kate Saenko
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #251
Composing Value Functions in Reinforcement Learning
Benjamin van Niekerk · Steven James · Adam Earle · Benjamin Rosman
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #252
Fast Context Adaptation via Meta-Learning
Luisa Zintgraf · Kyriacos Shiarlis · Vitaly Kurin · Katja Hofmann · Shimon Whiteson
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #253
Provable Guarantees for Gradient-Based Meta-Learning
Nina Balcan · Mikhail Khodak · Ameet Talwalkar
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #254
Towards Understanding Knowledge Distillation
Mary Phuong · Christoph H. Lampert
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #255
Transferable Adversarial Training: A General Approach to Adapting Deep Classifiers
Hong Liu · Mingsheng Long · Jianmin Wang · Michael Jordan
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #256
Transferability vs. Discriminability: Batch Spectral Penalization for Adversarial Domain Adaptation
Xinyang Chen · Sinan Wang · Mingsheng Long · Jianmin Wang
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #257
Learning-to-Learn Stochastic Gradient Descent with Biased Regularization
Giulia Denevi · Carlo Ciliberto · Riccardo Grazzi · Massimiliano Pontil
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #258
BERT and PALs: Projected Attention Layers for Efficient Adaptation in Multi-Task Learning
Asa Cooper Stickland · Iain Murray
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #259
Towards Accurate Model Selection in Deep Unsupervised Domain Adaptation
Kaichao You · Ximei Wang · Mingsheng Long · Michael Jordan
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #260
Active Embedding Search via Noisy Paired Comparisons
Gregory Canal · Andy Massimino · Mark Davenport · Christopher Rozell
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #261
Fast Direct Search in an Optimally Compressed Continuous Target Space for Efficient Multi-Label Active Learning
weishi shi · Qi Yu
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #262
Myopic Posterior Sampling for Adaptive Goal Oriented Design of Experiments
Kirthevasan Kandasamy · Willie Neiswanger · Reed Zhang · Akshay Krishnamurthy · Jeff Schneider · Barnabás Póczos
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #263
Bayesian Generative Active Deep Learning
Toan Tran · Thanh-Toan Do · Ian Reid · Gustavo Carneiro
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #264
Active Learning for Probabilistic Structured Prediction of Cuts and Matchings
Sima Behpour · Anqi Liu · Brian Ziebart
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #265
Active Learning with Disagreement Graphs
Corinna Cortes · Giulia DeSalvo · Mehryar Mohri · Ningshan Zhang · Claudio Gentile
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #266
Multi-Frequency Vector Diffusion Maps
Yifeng Fan · Zhizhen Zhao
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #267
Co-manifold learning with missing data
Gal Mishne · Eric Chi · Ronald Coifman
Poster
Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #268
Hybrid Models with Deep and Invertible Features
Eric Nalisnick · Akihiro Matsukawa · Yee Whye Teh · Dilan Gorur · Balaji Lakshminarayanan
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #1
State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations
Alex Lamb · Jonathan Binas · Anirudh Goyal · Sandeep Subramanian · Ioannis Mitliagkas · Yoshua Bengio · Michael Mozer
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #2
Variational Laplace Autoencoders
Yookoon Park · Chris Kim · Gunhee Kim
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #3
Latent Normalizing Flows for Discrete Sequences
Zachary Ziegler · Alexander Rush
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #4
Multi-objective training of Generative Adversarial Networks with multiple discriminators
Isabela Albuquerque · Joao Monteiro · Thang Doan · Breandan Considine · Tiago Falk · Ioannis Mitliagkas
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #5
Learning Discrete and Continuous Factors of Data via Alternating Disentanglement
Yeonwoo Jeong · Hyun Oh Song
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #6
Bit-Swap: Recursive Bits-Back Coding for Lossless Compression with Hierarchical Latent Variables
Friso Kingma · Pieter Abbeel · Jonathan Ho
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #7
Graphite: Iterative Generative Modeling of Graphs
Aditya Grover · Aaron Zweig · Stefano Ermon
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #9
MIWAE: Deep Generative Modelling and Imputation of Incomplete Data Sets
Pierre-Alexandre Mattei · Jes Frellsen
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #10
On Scalable and Efficient Computation of Large Scale Optimal Transport
Yujia Xie · Minshuo Chen · Haoming Jiang · Tuo Zhao · Hongyuan Zha
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #11
Understanding and correcting pathologies in the training of learned optimizers
Luke Metz · Niru Maheswaranathan · Jeremy Nixon · Daniel Freeman · Jascha Sohl-Dickstein
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #12
Demystifying Dropout
Hongchang Gao · Jian Pei · Heng Huang
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #13
Ladder Capsule Network
Taewon Jeong · Youngmin Lee · Heeyoung Kim
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #14
Unreproducible Research is Reproducible
Xavier Bouthillier · César Laurent · Pascal Vincent
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #15
Geometric Scattering for Graph Data Analysis
Feng Gao · Guy Wolf · Matthew Hirn
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #16
Robust Inference via Generative Classifiers for Handling Noisy Labels
Kimin Lee · Sukmin Yun · Kibok Lee · Honglak Lee · Bo Li · Jinwoo Shin
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #17
LIT: Learned Intermediate Representation Training for Model Compression
Animesh Koratana · Daniel Kang · Peter Bailis · Matei Zaharia
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #18
Analyzing and Improving Representations with the Soft Nearest Neighbor Loss
Nicholas Frosst · Nicolas Papernot · Geoffrey Hinton
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #19
What is the Effect of Importance Weighting in Deep Learning?
Jonathon Byrd · Zachary Lipton
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #20
Similarity of Neural Network Representations Revisited
Simon Kornblith · Mohammad Norouzi · Honglak Lee · Geoffrey Hinton
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #21
Learning Fast Algorithms for Linear Transforms Using Butterfly Factorizations
Tri Dao · Albert Gu · Matthew Eichhorn · Atri Rudra · Christopher Re
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #22
Distributed, Egocentric Representations of Graphs for Detecting Critical Structures
Ruo-Chun Tzeng · Shan-Hung (Brandon) Wu
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #23
Breaking the Softmax Bottleneck via Learnable Monotonic Pointwise Non-linearities
Octavian-Eugen Ganea · Sylvain Gelly · Gary Becigneul · Aliaksei Severyn
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #24
Multi-Object Representation Learning with Iterative Variational Inference
Klaus Greff · Raphael Lopez Kaufman · Rishabh Kabra · Nicholas Watters · Christopher Burgess · Daniel Zoran · Loic Matthey · Matthew Botvinick · Alexander Lerchner
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #25
Cross-Domain 3D Equivariant Image Embeddings
Carlos Esteves · Avneesh Sud · Zhengyi Luo · Kostas Daniilidis · Ameesh Makadia
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #26
Loss Landscapes of Regularized Linear Autoencoders
Daniel Kunin · Jonathan Bloom · Aleksandrina Goeva · Cotton Seed
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #27
Hyperbolic Disk Embeddings for Directed Acyclic Graphs
Ryota Suzuki · Ryusuke Takahama · Shun Onoda
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #28
LatentGNN: Learning Efficient Non-local Relations for Visual Recognition
Songyang Zhang · Xuming He · Shipeng Yan
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #29
Robustly Disentangled Causal Mechanisms: Validating Deep Representations for Interventional Robustness
Raphael Suter · Djordje Miladinovic · Bernhard Schölkopf · Stefan Bauer
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #30
Lorentzian Distance Learning for Hyperbolic Representations
Marc Law · Renjie Liao · Jake Snell · Richard Zemel
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #31
Batch Policy Learning under Constraints
Hoang Le · Cameron Voloshin · Yisong Yue
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #32
Quantifying Generalization in Reinforcement Learning
Karl Cobbe · Oleg Klimov · Chris Hesse · Taehoon Kim · John Schulman
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #33
Learning Latent Dynamics for Planning from Pixels
Danijar Hafner · Timothy Lillicrap · Ian Fischer · Ruben Villegas · David Ha · Honglak Lee · James Davidson
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #34
Projections for Approximate Policy Iteration Algorithms
Riad Akrour · Joni Pajarinen · Jan Peters · Gerhard Neumann
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #35
Learning Structured Decision Problems with Unawareness
Craig Innes · Alex Lascarides
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #36
Calibrated Model-Based Deep Reinforcement Learning
Ali Malik · Volodymyr Kuleshov · Jiaming Song · Danny Nemer · Harlan Seymour · Stefano Ermon
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #37
Reinforcement Learning in Configurable Continuous Environments
Alberto Maria Metelli · Emanuele Ghelfi · Marcello Restelli
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #38
Target-Based Temporal-Difference Learning
Donghwan Lee · Niao He
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #39
Iterative Linearized Control: Stable Algorithms and Complexity Guarantees
Vincent Roulet · Dmitriy Drusvyatskiy · Siddhartha Srinivasa · Zaid Harchaoui
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #40
Finding Options that Minimize Planning Time
Yuu Jinnai · David Abel · David Hershkowitz · Michael L. Littman · George Konidaris
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #41
Stochastic Beams and Where To Find Them: The Gumbel-Top-k Trick for Sampling Sequences Without Replacement
Wouter Kool · Herke van Hoof · Max Welling
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #42
Learning to Exploit Long-term Relational Dependencies in Knowledge Graphs
Lingbing Guo · Zequn Sun · Wei Hu
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #43
Meta-Learning Neural Bloom Filters
Jack Rae · Sergey Bartunov · Timothy Lillicrap
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #44
CoT: Cooperative Training for Generative Modeling of Discrete Data
Sidi Lu · Lantao Yu · Siyuan Feng · Yaoming Zhu · Weinan Zhang
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #45
Non-Monotonic Sequential Text Generation
Sean Welleck · Kiante Brantley · Hal Daume · Kyunghyun Cho
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #46
Insertion Transformer: Flexible Sequence Generation via Insertion Operations
Mitchell Stern · William Chan · Jamie Kiros · Jakob Uszkoreit
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #47
Empirical Analysis of Beam Search Performance Degradation in Neural Sequence Models
Eldan Cohen · Christopher Beck
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #48
Trainable Decoding of Sets of Sequences for Neural Sequence Models
Ashwin Kalyan · Peter Anderson · Stefan Lee · Dhruv Batra
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #49
Learning to Generalize from Sparse and Underspecified Rewards
Rishabh Agarwal · Chen Liang · Dale Schuurmans · Mohammad Norouzi
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #50
Efficient Training of BERT by Progressively Stacking
Linyuan Gong · Di He · Zhuohan Li · Tao Qin · Liwei Wang · Tie-Yan Liu
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #51
Decentralized Exploration in Multi-Armed Bandits
Raphael Feraud · REDA ALAMI · Romain Laroche
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #52
Warm-starting Contextual Bandits: Robustly Combining Supervised and Bandit Feedback
Chicheng Zhang · Alekh Agarwal · Hal Daume · John Langford · Sahand Negahban
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #53
Exploiting structure of uncertainty for efficient matroid semi-bandits
Pierre Perrault · Vianney Perchet · Michal Valko
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #54
PAC Identification of Many Good Arms in Stochastic Multi-Armed Bandits
Arghya Roy Chaudhuri · Shivaram Kalyanakrishnan
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #55
Contextual Multi-armed Bandit Algorithm for Semiparametric Reward Model
Gi-Soo Kim · Myunghee Cho Paik
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #56
Bayesian Action Decoder for Deep Multi-Agent Reinforcement Learning
Jakob Foerster · Francis Song · Edward Hughes · Neil Burch · Iain Dunning · Shimon Whiteson · Matthew Botvinick · Michael Bowling
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #57
TarMAC: Targeted Multi-Agent Communication
Abhishek Das · Theophile Gervet · Joshua Romoff · Dhruv Batra · Devi Parikh · Michael Rabbat · Joelle Pineau
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #58
QTRAN: Learning to Factorize with Transformation for Cooperative Multi-Agent Reinforcement Learning
Kyunghwan Son · Daewoo Kim · Wan Ju Kang · David Earl Hostallero · Yung Yi
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #59
Actor-Attention-Critic for Multi-Agent Reinforcement Learning
Shariq Iqbal · Fei Sha
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #60
Finite-Time Analysis of Distributed TD(0) with Linear Function Approximation on Multi-Agent Reinforcement Learning
Thinh Doan · Siva Maguluri · Justin Romberg
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #61
Neural Network Attributions: A Causal Perspective
Aditya Chattopadhyay · Piyushi Manupriya · Anirban Sarkar · Vineeth N Balasubramanian
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #62
Towards a Deep and Unified Understanding of Deep Neural Models in NLP
Chaoyu Guan · Xiting Wang · Quanshi Zhang · Runjin Chen · Di He · Xing Xie
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #63
Explaining Deep Neural Networks with a Polynomial Time Algorithm for Shapley Value Approximation
Marco Ancona · Cengiz Oztireli · Markus Gross
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #64
Functional Transparency for Structured Data: a Game-Theoretic Approach
Guang-He Lee · Wengong Jin · David Alvarez-Melis · Tommi Jaakkola
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #65
Exploring interpretable LSTM neural networks over multi-variable data
Tian Guo · Tao LIN · Nino Antulov-Fantulin
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #66
TensorFuzz: Debugging Neural Networks with Coverage-Guided Fuzzing
Augustus Odena · Catherine Olsson · David Andersen · Ian Goodfellow
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #67
Gaining Free or Low-Cost Interpretability with Interpretable Partial Substitute
Tong Wang
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #68
State-Regularized Recurrent Neural Networks
Cheng Wang · Mathias Niepert
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #69
Understanding Impacts of High-Order Loss Approximations and Features in Deep Learning Interpretation
Sahil Singla · Eric Wallace · Shi Feng · Soheil Feizi
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #70
On the Connection Between Adversarial Robustness and Saliency Map Interpretability
Christian Etmann · Sebastian Lunz · Peter Maass · Carola-Bibiane Schönlieb
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #71
Why do Larger Models Generalize Better? A Theoretical Perspective via the XOR Problem
Alon Brutzkus · Amir Globerson
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #72
On the Spectral Bias of Neural Networks
Nasim Rahaman · Aristide Baratin · Devansh Arpit · Felix Draxler · Min Lin · Fred Hamprecht · Yoshua Bengio · Aaron Courville
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #73
Recursive Sketches for Modular Deep Learning
Badih Ghazi · Rina Panigrahy · Joshua R. Wang
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #74
Zero-Shot Knowledge Distillation in Deep Networks
Gaurav Kumar Nayak · Konda Reddy Mopuri · Vaisakh Shaj · Venkatesh Babu Radhakrishnan · Anirban Chakraborty
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #75
A Convergence Theory for Deep Learning via Over-Parameterization
Zeyuan Allen-Zhu · Yuanzhi Li · Zhao Song
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #76
A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks
Umut Simsekli · Levent Sagun · Mert Gurbuzbalaban
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #77
Approximation and non-parametric estimation of ResNet-type convolutional neural networks
Kenta Oono · Taiji Suzuki
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #78
Global Convergence of Block Coordinate Descent in Deep Learning
Jinshan ZENG · Tsz Kit Lau · Shaobo Lin · Yuan Yao
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #79
Measurements of Three-Level Hierarchical Structure in the Outliers in the Spectrum of Deepnet Hessians
Vardan Papyan
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #80
On the Limitations of Representing Functions on Sets
Edward Wagstaff · Fabian Fuchs · Martin Engelcke · Herbert Ingmar Posner · Michael A Osborne
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #81
Probabilistic Neural Symbolic Models for Interpretable Visual Question Answering
Shanmukha Ramakrishna Vedantam · Karan Desai · Stefan Lee · Marcus Rohrbach · Dhruv Batra · Devi Parikh
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #82
Nonparametric Bayesian Deep Networks with Local Competition
Konstantinos Panousis · Sotirios Chatzis · Sergios Theodoridis
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #83
Good Initializations of Variational Bayes for Deep Models
Simone Rossi · Pietro Michiardi · Maurizio Filippone
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #84
Dropout as a Structured Shrinkage Prior
Eric Nalisnick · Jose Hernandez-Lobato · Padhraic Smyth
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #85
ARSM: Augment-REINFORCE-Swap-Merge Estimator for Gradient Backpropagation Through Categorical Variables
Mingzhang Yin · Yuguang Yue · Mingyuan Zhou
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #86
On Variational Bounds of Mutual Information
Ben Poole · Sherjil Ozair · Aäron van den Oord · Alexander Alemi · George Tucker
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #87
Partially Exchangeable Networks and Architectures for Learning Summary Statistics in Approximate Bayesian Computation
Samuel Wiqvist · Pierre-Alexandre Mattei · Umberto Picchini · Jes Frellsen
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #88
Hierarchical Importance Weighted Autoencoders
Chin-Wei Huang · Kris Sankaran · Eeshan Dhekane · Alexandre Lacoste · Aaron Courville
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #89
Faster Attend-Infer-Repeat with Tractable Probabilistic Models
Karl Stelzner · Robert Peharz · Kristian Kersting
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #90
Understanding Priors in Bayesian Neural Networks at the Unit Level
Mariia Vladimirova · Jakob Verbeek · Pablo Mesejo · Julyan Arbel
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #91
Defending Against Saddle Point Attack in Byzantine-Robust Distributed Learning
Dong Yin · Yudong Chen · Kannan Ramchandran · Peter Bartlett
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #92
Stochastic Iterative Hard Thresholding for Graph-structured Sparsity Optimization
Baojian Zhou · Feng Chen · Yiming Ying
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #93
Neuron birth-death dynamics accelerates gradient descent and converges asymptotically
Grant Rotskoff · Samy Jelassi · Joan Bruna · Eric Vanden-Eijnden
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #94
Width Provably Matters in Optimization for Deep Linear Neural Networks
Simon Du · Wei Hu
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #95
Overparameterized Nonlinear Learning: Gradient Descent Takes the Shortest Path?
Samet Oymak · Mahdi Soltanolkotabi
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #96
Power k-Means Clustering
Jason Xu · Kenneth Lange
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #97
Distributed Learning over Unreliable Networks
Chen Yu · Hanlin Tang · Cedric Renggli · Simon Kassing · Ankit Singla · Dan Alistarh · Ce Zhang · Ji Liu
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #98
Escaping Saddle Points with Adaptive Gradient Methods
Matthew Staib · Sashank Jakkam Reddi · Satyen Kale · Sanjiv Kumar · Suvrit Sra
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #99
$\texttt{DoubleSqueeze}$: Parallel Stochastic Gradient Descent with Double-pass Error-Compensated Compression
Hanlin Tang · Chen Yu · Xiangru Lian · Tong Zhang · Ji Liu
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #100
Model Function Based Conditional Gradient Method with Armijo-like Line Search
Peter Ochs · Yura Malitsky
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #101
Analogies Explained: Towards Understanding Word Embeddings
Carl Allen · Timothy Hospedales
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #102
Parameter-Efficient Transfer Learning for NLP
Neil Houlsby · Andrei Giurgiu · Stanislaw Jastrzebski · Bruna Morrone · Quentin de Laroussilhe · Andrea Gesmundo · Mona Attariyan · Sylvain Gelly
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #103
Efficient On-Device Models using Neural Projections
Sujith Ravi
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #104
Deep Residual Output Layers for Neural Language Generation
Nikolaos Pappas · James Henderson
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #105
Improving Neural Language Modeling via Adversarial Training
Dilin Wang · Chengyue Gong · Qiang Liu
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #106
Mixture Models for Diverse Machine Translation: Tricks of the Trade
Tianxiao Shen · Myle Ott · Michael Auli · Marc'Aurelio Ranzato
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #107
MASS: Masked Sequence to Sequence Pre-training for Language Generation
Kaitao Song · Xu Tan · Tao Qin · Jianfeng Lu · Tie-Yan Liu
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #108
Humor in Word Embeddings: Cockamamie Gobbledegook for Nincompoops
Limor Gultchin · Genevieve Patterson · Nancy Baym · Nathaniel Swinger · Adam Kalai
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #109
MeanSum: A Neural Model for Unsupervised Multi-Document Abstractive Summarization
Eric Chu · Peter Liu
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #110
CHiVE: Varying Prosody in Speech Synthesis with a Linguistically Driven Dynamic Hierarchical Conditional Variational Network
Tom Kenter · Vincent Wan · Chun-an Chan · Robert Clark · Jakub Vit
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #111
COMIC: Multi-view Clustering Without Parameter Selection
Xi Peng · Zhenyu Huang · Jiancheng Lv · Hongyuan Zhu · Joey Tianyi Zhou
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #112
The Wasserstein Transform
Facundo Memoli · Zane Smith · Zhengchao Wan
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #113
Sequential Facility Location: Approximate Submodularity and Greedy Algorithm
Ehsan Elhamifar
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #114
Neural Collaborative Subspace Clustering
Tong Zhang · Pan Ji · Mehrtash Harandi · Wenbing Huang · HONGDONG LI
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #115
Unsupervised Deep Learning by Neighbourhood Discovery
Jiabo Huang · Qi Dong · Shaogang Gong · Xiatian Zhu
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #116
Autoregressive Energy Machines
Conor Durkan · Charlie Nash
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #117
Greedy Orthogonal Pivoting Algorithm for Non-Negative Matrix Factorization
Kai Zhang · Sheng Zhang · Jun Liu · Jun Wang · Jie Zhang
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #118
Noise2Self: Blind Denoising by Self-Supervision
Joshua Batson · Loic Royer
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #119
Learning Dependency Structures for Weak Supervision Models
Paroma Varma · Frederic Sala · Ann He · Alexander J Ratner · Christopher Re
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #120
Geometry and Symmetry in Short-and-Sparse Deconvolution
Han-Wen Kuo · Yenson Lau · Yuqian Zhang · John Wright
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #121
On Sparse Linear Regression in the Local Differential Privacy Model
Di Wang · Jinhui Xu
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #122
Differentially Private Empirical Risk Minimization with Non-convex Loss Functions
Di Wang · Changyou Chen · Jinhui Xu
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #123
Bounding User Contributions: A Bias-Variance Trade-off in Differential Privacy
Kareem Amin · Alex Kulesza · andres munoz · Sergei Vassilvitskii
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #124
Differentially Private Learning of Geometric Concepts
Haim Kaplan · Yishay Mansour · Yossi Matias · Uri Stemmer
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #125
Toward Controlling Discrimination in Online Ad Auctions
Elisa Celis · Anay Mehrotra · Nisheeth Vishnoi
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #126
Learning Optimal Fair Policies
Razieh Nabi · Daniel Malinsky · Ilya Shpitser
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #127
Fairness-Aware Learning for Continuous Attributes and Treatments
Jeremie Mary · Clément Calauzènes · Noureddine El Karoui
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #128
Fairness risk measures
Robert C Williamson · Aditya Menon
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #129
Proportionally Fair Clustering
Xingyu Chen · Brandon Fain · Liang Lyu · Kamesh Munagala
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #130
Stable and Fair Classification
Lingxiao Huang · Nisheeth Vishnoi
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #131
Flexibly Fair Representation Learning by Disentanglement
Elliot Creager · David Madras · Joern-Henrik Jacobsen · Marissa Weis · Kevin Swersky · Toniann Pitassi · Richard Zemel
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #132
Fair Regression: Quantitative Definitions and Reduction-Based Algorithms
Alekh Agarwal · Miroslav Dudik · Zhiwei Steven Wu
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #133
Fairness without Harm: Decoupled Classifiers with Preference Guarantees
Berk Ustun · Yang Liu · David Parkes
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #134
Differentially Private Fair Learning
Matthew Jagielski · Michael Kearns · Jieming Mao · Alina Oprea · Aaron Roth · Saeed Sharifi-Malvajerdi · Jonathan Ullman
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #135
Obtaining Fairness using Optimal Transport Theory
Paula Gordaliza · Eustasio del Barrio · Gamboa Fabrice · Loubes Jean-Michel
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #136
Repairing without Retraining: Avoiding Disparate Impact with Counterfactual Distributions
Hao Wang · Berk Ustun · Flavio Calmon
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #137
On the Long-term Impact of Algorithmic Decision Policies: Effort Unfairness and Feature Segregation through Social Learning
Hoda Heidari · Vedant Nanda · Krishna Gummadi
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #138
Making Decisions that Reduce Discriminatory Impacts
Matt J. Kusner · Chris Russell · Joshua Loftus · Ricardo Silva
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #139
Submodular Maximization beyond Non-negativity: Guarantees, Fast Algorithms, and Applications
Christopher Harshaw · Moran Feldman · Justin Ward · Amin Karbasi
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #140
Online Algorithms for Rent-Or-Buy with Expert Advice
Sreenivas Gollapudi · Debmalya Panigrahi
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #141
Non-monotone Submodular Maximization with Nearly Optimal Adaptivity and Query Complexity
Matthew Fahrbach · Vahab Mirrokni · Morteza Zadimoghaddam
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #142
Categorical Feature Compression via Submodular Optimization
Mohammad Hossein Bateni · Lin Chen · Hossein Esfandiari · Gang Fu · Vahab Mirrokni · Afshin Rostamizadeh
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #143
Multi-Frequency Phase Synchronization
Tingran Gao · Zhizhen Zhao
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #144
Faster Algorithms for Binary Matrix Factorization
Ravi Kumar · Rina Panigrahy · Ali Rahimi · David Woodruff
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #146
Guided evolutionary strategies: augmenting random search with surrogate gradients
Niru Maheswaranathan · Luke Metz · George Tucker · Dami Choi · Jascha Sohl-Dickstein
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #147
Adaptive and Safe Bayesian Optimization in High Dimensions via One-Dimensional Subspaces
Johannes Kirschner · Mojmir Mutny · Nicole Hiller · Rasmus Ischebeck · Andreas Krause
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #148
Semi-Cyclic Stochastic Gradient Descent
Hubert Eichner · Tomer Koren · H. Brendan McMahan · Nati Srebro · Kunal Talwar
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #149
Matrix-Free Preconditioning in Online Learning
Ashok Cutkosky · Tamas Sarlos
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #150
Online Convex Optimization in Adversarial Markov Decision Processes
Aviv Rosenberg · Yishay Mansour
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #151
Competing Against Nash Equilibria in Adversarially Changing Zero-Sum Games
Adrian Rivera Cardoso · Jacob Abernethy · He Wang · Huan Xu
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #152
Online Learning with Sleeping Experts and Feedback Graphs
Corinna Cortes · Giulia DeSalvo · Claudio Gentile · Mehryar Mohri · Scott Yang
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #153
Incremental Randomized Sketching for Online Kernel Learning
Xiao Zhang · Shizhong Liao
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #154
Adaptive Scale-Invariant Online Algorithms for Learning Linear Models
Michal Kempka · Wojciech Kotlowski · Manfred K. Warmuth
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #155
Online Control with Adversarial Disturbances
Naman Agarwal · Brian Bullins · Elad Hazan · Sham Kakade · Karan Singh
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #156
Adversarial Online Learning with noise
Alon Resler · Yishay Mansour
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #157
Online Variance Reduction with Mixtures
Zalán Borsos · Sebastian Curi · Yehuda Levy · Andreas Krause
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #158
Bandit Multiclass Linear Classification: Efficient Algorithms for the Separable Case
Alina Beygelzimer · David Pal · Balazs Szorenyi · Devanathan Thiruvenkatachari · Chen-Yu Wei · Chicheng Zhang
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #159
Learning Linear-Quadratic Regulators Efficiently with only $\sqrt{T}$ Regret
Alon Cohen · Tomer Koren · Yishay Mansour
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #160
Learning from Delayed Outcomes via Proxies with Applications to Recommender Systems
Timothy Mann · Sven Gowal · Andras Gyorgy · Huiyi Hu · Ray Jiang · Balaji Lakshminarayanan · Prav Srinivasan
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #161
Adaptive Regret of Convex and Smooth Functions
Lijun Zhang · Tie-Yan Liu · Zhi-Hua Zhou
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #162
Online Adaptive Principal Component Analysis and Its extensions
Jianjun Yuan · Andrew Lamperski
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #163
POLITEX: Regret Bounds for Policy Iteration using Expert Prediction
Yasin Abbasi-Yadkori · Peter Bartlett · Kush Bhatia · Nevena Lazic · Csaba Szepesvari · Gellért Weisz
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #164
Anytime Online-to-Batch, Optimism and Acceleration
Ashok Cutkosky
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #165
Cautious Regret Minimization: Online Optimization with Long-Term Budget Constraints
Nikolaos Liakopoulos · Apostolos Destounis · Georgios Paschos · Thrasyvoulos Spyropoulos · Panayotis Mertikopoulos
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #166
Optimal Kronecker-Sum Approximation of Real Time Recurrent Learning
Frederik Benzing · Marcelo Matheus Gauy · Asier Mujika · Anders Martinsson · Angelika Steger
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #167
Adaptive Sensor Placement for Continuous Spaces
James Grant · Alexis Boukouvalas · Ryan-Rhys Griffiths · David Leslie · Sattar Vakili · Enrique Munoz De Cote
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #168
Scale-free adaptive planning for deterministic dynamics & discounted rewards
Peter Bartlett · Victor Gabillon · Jennifer A Healey · Michal Valko
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #169
Communication-Constrained Inference and the Role of Shared Randomness
Jayadev Acharya · Clément Canonne · Himanshu Tyagi
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #170
Learning and Data Selection in Big Datasets
Hossein Shokri Ghadikolaei · Hadi Ghauch · Inst. of Technology Carlo Fischione · Mikael Skoglund
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #171
Sublinear quantum algorithms for training linear and kernel-based classifiers
Tongyang Li · Shouvanik Chakrabarti · Xiaodi Wu
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #172
Agnostic Federated Learning
Mehryar Mohri · Gary Sivek · Ananda Suresh
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #173
Discovering Conditionally Salient Features with Statistical Guarantees
Jaime Roquero Gimenez · James Zou
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #174
A Theoretical Analysis of Contrastive Unsupervised Representation Learning
Nikunj Umesh Saunshi · Orestis Plevrakis · Sanjeev Arora · Mikhail Khodak · Hrishikesh Khandeparkar
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #175
The information-theoretic value of unlabeled data in semi-supervised learning
Alexander Golovnev · David Pal · Balazs Szorenyi
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #176
Unsupervised Label Noise Modeling and Loss Correction
Eric Arazo · Diego Ortego · Paul Albert · Noel O'Connor · Kevin McGuinness
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #177
Domain Adaptation with Asymmetrically-Relaxed Distribution Alignment
Yifan Wu · Ezra Winston · Divyansh Kaushik · Zachary Lipton
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #178
Pareto Optimal Streaming Unsupervised Classification
Soumya Basu · Steven Gutstein · Brent Lance · Sanjay Shakkottai
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #179
Geometric Losses for Distributional Learning
Arthur Mensch · Mathieu Blondel · Gabriel Peyré
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #180
Classification from Positive, Unlabeled and Biased Negative Data
Yu-Guan Hsieh · Gang Niu · Masashi Sugiyama
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #181
Complementary-Label Learning for Arbitrary Losses and Models
Takashi Ishida · Gang Niu · Aditya Menon · Masashi Sugiyama
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #182
Learning to Infer Program Sketches
Maxwell Nye · Luke Hewitt · Josh Tenenbaum · Armando Solar-Lezama
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #183
Hierarchically Structured Meta-learning
Huaxiu Yao · Ying WEI · Junzhou Huang · Zhenhui (Jessie) Li
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #184
Bridging Theory and Algorithm for Domain Adaptation
Yuchen Zhang · Tianle Liu · Mingsheng Long · Michael Jordan
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #185
Transfer Learning for Related Reinforcement Learning Tasks via Image-to-Image Translation
Shani Gamrian · Yoav Goldberg
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #186
Learning What and Where to Transfer
Yunhun Jang · Hankook Lee · Sung Ju Hwang · Jinwoo Shin
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #187
DBSCAN++: Towards fast and scalable density clustering
Jennifer Jang · Heinrich Jiang
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #188
Concrete Autoencoders: Differentiable Feature Selection and Reconstruction
Muhammed Fatih Balın · Abubakar Abid · James Zou
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #189
Gromov-Wasserstein Learning for Graph Matching and Node Embedding
Hongteng Xu · Dixin Luo · Hongyuan Zha · Lawrence Carin
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #190
Spectral Clustering of Signed Graphs via Matrix Power Means
Pedro Mercado · Francesco Tudisco · Matthias Hein
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #191
Coresets for Ordered Weighted Clustering
Vladimir Braverman · Shaofeng Jiang · Robert Krauthgamer · Xuan Wu
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #192
Fair k-Center Clustering for Data Summarization
Matthäus Kleindessner · Pranjal Awasthi · Jamie Morgenstern
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #193
A Better k-means++ Algorithm via Local Search
Silvio Lattanzi · Christian Sohler
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #194
Kernel Normalized Cut: a Theoretical Revisit
Yoshikazu Terada · Michio Yamamoto
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #195
Guarantees for Spectral Clustering with Fairness Constraints
Matthäus Kleindessner · Samira Samadi · Pranjal Awasthi · Jamie Morgenstern
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #196
Supervised Hierarchical Clustering with Exponential Linkage
Nishant Yadav · Ari Kobren · Nicholas Monath · Andrew McCallum
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #197
Sliced-Wasserstein Flows: Nonparametric Generative Modeling via Optimal Transport and Diffusions
Antoine Liutkus · Umut Simsekli · Szymon Majewski · Alain Durmus · Fabian-Robert Stöter
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #198
Non-Asymptotic Analysis of Fractional Langevin Monte Carlo for Non-Convex Optimization
Thanh Huy Nguyen · Umut Simsekli · Gaël RICHARD
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #199
Unifying Orthogonal Monte Carlo Methods
Krzysztof Choromanski · Mark Rowland · Wenyu Chen · Adrian Weller
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #200
Adaptive Monte Carlo Multiple Testing via Multi-Armed Bandits
Martin Zhang · James Zou · David Tse
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #201
Metropolis-Hastings Generative Adversarial Networks
Ryan Turner · Jane Hung · Eric Frank · Yunus Saatchi · Jason Yosinski
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #202
Scalable Metropolis-Hastings for Exact Bayesian Inference with Large Datasets
Rob Cornish · Paul Vanetti · Alexandre Bouchard-Côté · George Deligiannidis · Arnaud Doucet
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #203
Replica Conditional Sequential Monte Carlo
Alex Shestopaloff · Arnaud Doucet
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #204
A Polynomial Time MCMC Method for Sampling from Continuous Determinantal Point Processes
Alireza Rezaei · Shayan Oveis Gharan
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #205
Adaptive Antithetic Sampling for Variance Reduction
Hongyu Ren · Shengjia Zhao · Stefano Ermon
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #206
Accelerated Flow for Probability Distributions
Amirhossein Taghvaei · Prashant Mehta
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #207
Tight Kernel Query Complexity of Kernel Ridge Regression and Kernel $k$-means Clustering
Taisuke Yasuda · David Woodruff · Manuel Fernandez
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #208
Dimensionality Reduction for Tukey Regression
Kenneth Clarkson · Ruosong Wang · David Woodruff
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #209
Efficient Full-Matrix Adaptive Regularization
Naman Agarwal · Brian Bullins · Xinyi Chen · Elad Hazan · Karan Singh · Cyril Zhang · Yi Zhang
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #210
Breaking the gridlock in Mixture-of-Experts: Consistent and Efficient Algorithms
Ashok Makkuva · Pramod Viswanath · Sreeram Kannan · Sewoong Oh
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #211
Efficient Nonconvex Regularized Tensor Completion with Structure-aware Proximal Iterations
Quanming Yao · James Kwok · Bo Han
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #212
Robust Estimation of Tree Structured Gaussian Graphical Models
Ashish Katiyar · Jessica Hoffmann · Constantine Caramanis
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #213
Spectral Approximate Inference
Sejun Park · Eunho Yang · Se-Young Yun · Jinwoo Shin
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #214
Partially Linear Additive Gaussian Graphical Models
Sinong Geng · Minhao Yan · Mladen Kolar · Sanmi Koyejo
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #215
DAG-GNN: DAG Structure Learning with Graph Neural Networks
Yue Yu · Jie Chen · Tian Gao · Mo Yu
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #216
Random Walks on Hypergraphs with Edge-Dependent Vertex Weights
Uthsav Chitra · Benjamin Raphael
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #217
Doubly Robust Joint Learning for Recommendation on Data Missing Not at Random
Xiaojie Wang · Rui Zhang · Yu Sun · Jianzhong Qi
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #218
Linear-Complexity Data-Parallel Earth Mover's Distance Approximations
Kubilay Atasu · Thomas Mittelholzer
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #219
Model Comparison for Semantic Grouping
Francisco Vargas · Kamen Brestnichki · Nils Hammerla
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #220
RaFM: Rank-Aware Factorization Machines
Xiaoshuang Chen · Yin Zheng · Jiaxing Wang · Wenye Ma · Junzhou Huang
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #221
CAB: Continuous Adaptive Blending for Policy Evaluation and Learning
Yi Su · Lequn Wang · Michele Santacatterina · Thorsten Joachims
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #222
MetricGAN: Generative Adversarial Networks based Black-box Metric Scores Optimization for Speech Enhancement
Szu-Wei Fu · Chien-Feng Liao · Yu Tsao · Shou-De Lin
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #223
Neural Separation of Observed and Unobserved Distributions
Tavi Halperin · Ariel Ephrat · Yedid Hoshen
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #224
Almost Unsupervised Text to Speech and Automatic Speech Recognition
Yi Ren · Xu Tan · Tao Qin · Sheng Zhao · Zhou Zhao · Tie-Yan Liu
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #225
AutoVC: Zero-Shot Voice Style Transfer with Only Autoencoder Loss
Kaizhi Qian · Yang Zhang · Shiyu Chang · Xuesong Yang · Mark Hasegawa-Johnson
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #226
A fully differentiable beam search decoder
Ronan Collobert · Awni Hannun · Gabriel Synnaeve
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #227
Scaling Up Ordinal Embedding: A Landmark Approach
Jesse Anderton · Javed Aslam
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #228
Learning to select for a predefined ranking
Aleksei Ustimenko · Aleksandr Vorobev · Gleb Gusev · Pavel Serdyukov
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #229
Mallows ranking models: maximum likelihood estimate and regeneration
Wenpin Tang
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #230
Fast and Stable Maximum Likelihood Estimation for Incomplete Multinomial Models
Chenyang ZHANG · Guosheng Yin
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #231
Fast Algorithm for Generalized Multinomial Models with Ranking Data
Jiaqi Gu · Guosheng Yin
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #232
Graph Resistance and Learning from Pairwise Comparisons
Julien Hendrickx · Alexander Olshevsky · Venkatesh Saligrama
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #233
Learning Context-dependent Label Permutations for Multi-label Classification
Jinseok Nam · Young-Bum Kim · Eneldo Loza Mencia · Sunghyun Park · Ruhi Sarikaya · Johannes Fürnkranz
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #234
Discovering Context Effects from Raw Choice Data
Arjun Seshadri · Alexander Peysakhovich · Johan Ugander
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #235
On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference
Rohin Shah · Noah Gundotra · Pieter Abbeel · EECS Anca Dragan
Poster
Thu Jun 13th 06:30 -- 09:00 PM @ Pacific Ballroom #236
Learning Distance for Sequences by Learning a Ground Metric
Bing Su · Ying Wu