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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