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Invited Talk
Wed Jul 11 12:00 AM -- 01:00 AM (PDT) @ A1
AI and Security: Lessons, Challenges and Future Directions
Dawn Song
[ Video] 
Session
Wed Jul 11 01:00 AM -- 01:20 AM (PDT) @ A1
Best Paper Session 1
Oral
Wed Jul 11 02:00 AM -- 02:20 AM (PDT) @ A5
Predict and Constrain: Modeling Cardinality in Deep Structured Prediction
In Structured Prediction 1
Nataly Brukhim · Amir Globerson
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:00 AM -- 02:20 AM (PDT) @ A9
Optimal Tuning for Divide-and-conquer Kernel Ridge Regression with Massive Data
In Parallel and Distributed Learning 1
Ganggang Xu · Zuofeng Shang · Guang Cheng
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:00 AM -- 02:20 AM (PDT) @ A6
Nonparametric Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information
In Statistical Learning Theory 1
Yichong Xu · Hariank Muthakana · Sivaraman Balakrishnan · Aarti Singh · Artur Dubrawski
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:00 AM -- 02:20 AM (PDT) @ A7
Learning Continuous Hierarchies in the Lorentz Model of Hyperbolic Geometry
In Representation Learning 1
Maximilian Nickel · Douwe Kiela
[ PDF] 
Oral
Wed Jul 11 02:00 AM -- 02:20 AM (PDT) @ K11
Equivalence of Multicategory SVM and Simplex Cone SVM: Fast Computations and Statistical Theory
In Clustering 1
Guillaume Pouliot
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:00 AM -- 02:20 AM (PDT) @ A4
Crowdsourcing with Arbitrary Adversaries
In Unsupervised Learning 1
Matthäus Kleindessner · Pranjal Awasthi
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:00 AM -- 02:20 AM (PDT) @ Victoria
DiCE: The Infinitely Differentiable Monte Carlo Estimator
In Deep Learning (Neural Network Architectures) 1
Jakob Foerster · Gregory Farquhar · Maruan Al-Shedivat · Tim Rocktäschel · Eric Xing · Shimon Whiteson
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:00 AM -- 02:20 AM (PDT) @ K1 + K2
Learning to Explain: An Information-Theoretic Perspective on Model Interpretation
In Feature Selection 1
Jianbo Chen · Le Song · Martin Wainwright · Michael Jordan
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:00 AM -- 02:20 AM (PDT) @ A3
Transfer Learning via Learning to Transfer
In Transfer and Multi-Task Learning 1
Ying WEI · Yu Zhang · Junzhou Huang · Qiang Yang
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:00 AM -- 02:20 AM (PDT) @ A1
Problem Dependent Reinforcement Learning Bounds Which Can Identify Bandit Structure in MDPs
In Reinforcement Learning 1
Andrea Zanette · Emma Brunskill
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:20 AM -- 02:40 AM (PDT) @ A5
SparseMAP: Differentiable Sparse Structured Inference
In Structured Prediction 1
Vlad Niculae · Andre Filipe Torres Martins · Mathieu Blondel · Claire Cardie
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:20 AM -- 02:30 AM (PDT) @ A9
Distributed Nonparametric Regression under Communication Constraints
In Parallel and Distributed Learning 1
Yuancheng Zhu · John Lafferty
[ PDF] 
Oral
Wed Jul 11 02:20 AM -- 02:30 AM (PDT) @ A1
Learning with Abandonment
In Reinforcement Learning 1
Sven Schmit · Ramesh Johari
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:20 AM -- 02:30 AM (PDT) @ A7
Hyperbolic Entailment Cones for Learning Hierarchical Embeddings
In Representation Learning 1
Octavian-Eugen Ganea · Gary Becigneul · Thomas Hofmann
[ PDF] 
Oral
Wed Jul 11 02:20 AM -- 02:30 AM (PDT) @ A6
Do Outliers Ruin Collaboration?
In Statistical Learning Theory 1
Mingda Qiao
[ PDF] 
Oral
Wed Jul 11 02:20 AM -- 02:30 AM (PDT) @ Victoria
Learning to search with MCTSnets
In Deep Learning (Neural Network Architectures) 1
Arthur Guez · Theophane Weber · Ioannis Antonoglou · Karen Simonyan · Oriol Vinyals · Daan Wierstra · Remi Munos · David Silver
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:20 AM -- 02:30 AM (PDT) @ K1 + K2
Nonoverlap-Promoting Variable Selection
In Feature Selection 1
Pengtao Xie · Hongbao Zhang · Yichen Zhu · Eric Xing
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:20 AM -- 02:40 AM (PDT) @ A3
Meta-Learning by Adjusting Priors Based on Extended PAC-Bayes Theory
In Transfer and Multi-Task Learning 1
Ron Amit · Ron Meir
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:20 AM -- 02:30 AM (PDT) @ K11
Quickshift++: Provably Good Initializations for Sample-Based Mean Shift
In Clustering 1
Heinrich Jiang · Jennifer Jang · Samory Kpotufe
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:20 AM -- 02:30 AM (PDT) @ A4
Analysis of Minimax Error Rate for Crowdsourcing and Its Application to Worker Clustering Model
In Unsupervised Learning 1
Hideaki Imamura · Issei Sato · Masashi Sugiyama
[ PDF] 
Oral
Wed Jul 11 02:30 AM -- 02:40 AM (PDT) @ K1 + K2
MSplit LBI: Realizing Feature Selection and Dense Estimation Simultaneously in Few-shot and Zero-shot Learning
In Feature Selection 1
Bo Zhao · Xinwei Sun · Yanwei Fu · Yuan Yao · Yizhou Wang
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:30 AM -- 02:40 AM (PDT) @ A4
Conditional Noise-Contrastive Estimation of Unnormalised Models
In Unsupervised Learning 1
Ciwan Ceylan · Michael Gutmann
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:30 AM -- 02:40 AM (PDT) @ K11
Hierarchical Clustering with Structural Constraints
In Clustering 1
Evangelos Chatziafratis · Rad Niazadeh · Moses Charikar
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:30 AM -- 02:40 AM (PDT) @ A6
LeapsAndBounds: A Method for Approximately Optimal Algorithm Configuration
In Statistical Learning Theory 1
Gellért Weisz · András György · Csaba Szepesvari
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:30 AM -- 02:40 AM (PDT) @ A7
Tree Edit Distance Learning via Adaptive Symbol Embeddings
In Representation Learning 1
Benjamin Paaßen · Claudio Gallicchio · Alessio Micheli · CITEC Barbara Hammer
[ PDF] 
Oral
Wed Jul 11 02:30 AM -- 02:40 AM (PDT) @ A1
Lipschitz Continuity in Model-based Reinforcement Learning
In Reinforcement Learning 1
Kavosh Asadi · Dipendra Misra · Michael L. Littman
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:30 AM -- 02:40 AM (PDT) @ A9
Coded Sparse Matrix Multiplication
In Parallel and Distributed Learning 1
Sinong Wang · Jiashang Liu · Ness Shroff
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:30 AM -- 02:40 AM (PDT) @ Victoria
Differentiable plasticity: training plastic neural networks with backpropagation
In Deep Learning (Neural Network Architectures) 1
Thomas Miconi · Kenneth Stanley · Jeff Clune
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:40 AM -- 02:50 AM (PDT) @ A9
Towards More Efficient Stochastic Decentralized Learning: Faster Convergence and Sparse Communication
In Parallel and Distributed Learning 1
Zebang Shen · Aryan Mokhtari · Tengfei Zhou · Peilin Zhao · Hui Qian
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:40 AM -- 02:50 AM (PDT) @ A3
Bilevel Programming for Hyperparameter Optimization and Meta-Learning
In Transfer and Multi-Task Learning 1
Luca Franceschi · Paolo Frasconi · Saverio Salzo · Riccardo Grazzi · Massimiliano Pontil
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:40 AM -- 02:50 AM (PDT) @ A6
Variational Network Inference: Strong and Stable with Concrete Support
In Statistical Learning Theory 1
Amir Dezfouli · Edwin Bonilla · Richard Nock
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:40 AM -- 02:50 AM (PDT) @ K11
K-means clustering using random matrix sparsification
In Clustering 1
Kaushik Sinha
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:40 AM -- 02:50 AM (PDT) @ A7
Learning K-way D-dimensional Discrete Codes for Compact Embedding Representations
In Representation Learning 1
Ting Chen · Martin Min · Yizhou Sun
[ PDF] 
Oral
Wed Jul 11 02:40 AM -- 02:50 AM (PDT) @ K1 + K2
Black Box FDR
In Feature Selection 1
Wesley Tansey · Yixin Wang · David Blei · Raul Rabadan
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:40 AM -- 02:50 AM (PDT) @ Victoria
TACO: Learning Task Decomposition via Temporal Alignment for Control
In Deep Learning (Neural Network Architectures) 1
Kyriacos Shiarlis · Markus Wulfmeier · Sasha Salter · Shimon Whiteson · Ingmar Posner
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:40 AM -- 02:50 AM (PDT) @ A5
Efficient and Consistent Adversarial Bipartite Matching
In Structured Prediction 1
Rizal Fathony · Sima Behpour · Xinhua Zhang · Brian Ziebart
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:40 AM -- 02:50 AM (PDT) @ A4
Deep One-Class Classification
In Unsupervised Learning 1
Lukas Ruff · Nico Görnitz · Lucas Deecke · Shoaib Ahmed Siddiqui · Robert Vandermeulen · Alexander Binder · Emmanuel Müller · Marius Kloft
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:40 AM -- 02:50 AM (PDT) @ A1
Implicit Quantile Networks for Distributional Reinforcement Learning
In Reinforcement Learning 1
Will Dabney · Georg Ostrovski · David Silver · Remi Munos
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:50 AM -- 03:00 AM (PDT) @ A5
Learning to Speed Up Structured Output Prediction
In Structured Prediction 1
Xingyuan Pan · Vivek Srikumar
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:50 AM -- 03:00 AM (PDT) @ K1 + K2
Variable Selection via Penalized Neural Network: a Drop-Out-One Loss Approach
In Feature Selection 1
Mao Ye · Yan Sun
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:50 AM -- 03:00 AM (PDT) @ Victoria
Graph Networks as Learnable Physics Engines for Inference and Control
In Deep Learning (Neural Network Architectures) 1
Alvaro Sanchez-Gonzalez · Nicolas Heess · Jost Springenberg · Josh Merel · Martin Riedmiller · Raia Hadsell · Peter Battaglia
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:50 AM -- 03:00 AM (PDT) @ K11
Clustering Semi-Random Mixtures of Gaussians
In Clustering 1
Aravindan Vijayaraghavan · Pranjal Awasthi
[ PDF]  [ PDF]  [ Video] 
Oral
Wed Jul 11 02:50 AM -- 03:00 AM (PDT) @ A3
Pseudo-task Augmentation: From Deep Multitask Learning to Intratask Sharing—and Back
In Transfer and Multi-Task Learning 1
Elliot Meyerson · Risto Miikkulainen
[ PDF] 
Oral
Wed Jul 11 02:50 AM -- 03:00 AM (PDT) @ A9
Faster Derivative-Free Stochastic Algorithm for Shared Memory Machines
In Parallel and Distributed Learning 1
Bin Gu · Zhouyuan Huo · Cheng Deng · Heng Huang
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:50 AM -- 03:00 AM (PDT) @ A1
More Robust Doubly Robust Off-policy Evaluation
In Reinforcement Learning 1
Mehrdad Farajtabar · Yinlam Chow · Mohammad Ghavamzadeh
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:50 AM -- 03:00 AM (PDT) @ A4
Deep Density Destructors
In Unsupervised Learning 1
David Inouye · Pradeep Ravikumar
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:50 AM -- 03:00 AM (PDT) @ A6
Network Global Testing by Counting Graphlets
In Statistical Learning Theory 1
Jiashun Jin · Zheng Ke · Shengming Luo
[ PDF]  [ Video] 
Oral
Wed Jul 11 02:50 AM -- 03:00 AM (PDT) @ A7
CoVeR: Learning Covariate-Specific Vector Representations with Tensor Decompositions
In Representation Learning 1
Kevin Tian · Teng Zhang · James Zou
[ PDF] 
Oral
Wed Jul 11 04:30 AM -- 04:50 AM (PDT) @ K11
Leveraging Well-Conditioned Bases: Streaming and Distributed Summaries in Minkowski $p$-Norms
In Dimensionality Reduction 1
Charlie Dickens · Graham Cormode · David Woodruff
[ PDF]  [ PDF]  [ Video] 
Oral
Wed Jul 11 04:30 AM -- 04:50 AM (PDT) @ A5
WHInter: A Working set algorithm for High-dimensional sparse second order Interaction models
In Sparsity and Compressed Sensing 1
Marine LE MORVAN · Jean-Philippe Vert
[ PDF]  [ Video] 
Oral
Wed Jul 11 04:30 AM -- 04:50 AM (PDT) @ A1
Coordinated Exploration in Concurrent Reinforcement Learning
In Reinforcement Learning 2
Maria Dimakopoulou · Benjamin Van Roy
[ PDF]  [ Video] 
Oral
Wed Jul 11 04:30 AM -- 04:50 AM (PDT) @ A3
Stagewise Safe Bayesian Optimization with Gaussian Processes
In Optimization (Bayesian) 1
Yanan Sui · Vincent Zhuang · Joel Burdick · Yisong Yue
[ PDF] 
Oral
Wed Jul 11 04:30 AM -- 04:50 AM (PDT) @ K1 + K2
Limits of Estimating Heterogeneous Treatment Effects: Guidelines for Practical Algorithm Design
In Other Applications 1
Ahmed M. Alaa · Mihaela van der Schaar
[ PDF]  [ Video] 
Oral
Wed Jul 11 04:30 AM -- 04:50 AM (PDT) @ A6
Data-Dependent Stability of Stochastic Gradient Descent
In Statistical Learning Theory 2
Ilja Kuzborskij · Christoph H. Lampert
[ PDF]  [ Video] 
Oral
Wed Jul 11 04:30 AM -- 04:50 AM (PDT) @ A4
Markov Modulated Gaussian Cox Processes for Semi-Stationary Intensity Modeling of Events Data
In Gaussian Processes 1
Minyoung Kim
[ PDF]  [ Video] 
Oral
Wed Jul 11 04:30 AM -- 04:50 AM (PDT) @ Victoria
RadialGAN: Leveraging multiple datasets to improve target-specific predictive models using Generative Adversarial Networks
In Deep Learning (Neural Network Architectures) 2
Jinsung Yoon · James Jordon · Mihaela van der Schaar
[ PDF]  [ Video] 
Oral
Wed Jul 11 04:30 AM -- 04:50 AM (PDT) @ A9
Asynchronous Decentralized Parallel Stochastic Gradient Descent
In Optimization (Non-convex) 1
Xiangru Lian · Wei Zhang · Ce Zhang · Ji Liu
[ PDF]  [ Video] 
Oral
Wed Jul 11 04:30 AM -- 04:50 AM (PDT) @ A7
Improving Optimization in Models With Continuous Symmetry Breaking
In Representation Learning 2
Robert Bamler · Stephan Mandt
[ PDF] 
Oral
Wed Jul 11 04:50 AM -- 05:10 AM (PDT) @ A7
A probabilistic framework for multi-view feature learning with many-to-many associations via neural networks
In Representation Learning 2
Akifumi Okuno · Tetsuya Hada · Hidetoshi Shimodaira
[ PDF] 
Oral
Wed Jul 11 04:50 AM -- 05:10 AM (PDT) @ K11
Subspace Embedding and Linear Regression with Orlicz Norm
In Dimensionality Reduction 1
Alexandr Andoni · Chengyu Lin · Ying Sheng · Peilin Zhong · Ruiqi Zhong
[ PDF]  [ Video] 
Oral
Wed Jul 11 04:50 AM -- 05:10 AM (PDT) @ A9
signSGD: Compressed Optimisation for Non-Convex Problems
In Optimization (Non-convex) 1
Jeremy Bernstein · Yu-Xiang Wang · Kamyar Azizzadenesheli · Anima Anandkumar
[ PDF]  [ Video] 
Oral
Wed Jul 11 04:50 AM -- 05:10 AM (PDT) @ A3
BOCK : Bayesian Optimization with Cylindrical Kernels
In Optimization (Bayesian) 1
ChangYong Oh · Efstratios Gavves · Max Welling
[ PDF] 
Oral
Wed Jul 11 04:50 AM -- 05:10 AM (PDT) @ Victoria
Semi-Supervised Learning via Compact Latent Space Clustering
In Deep Learning (Neural Network Architectures) 2
Konstantinos Kamnitsas · Daniel C. Castro · Loic Le Folgoc · Ian Walker · Ryutaro Tanno · Daniel Rueckert · Ben Glocker · Antonio Criminisi · Aditya Nori
[ PDF]  [ Video] 
Oral
Wed Jul 11 04:50 AM -- 05:10 AM (PDT) @ A5
Nearly Optimal Robust Subspace Tracking
In Sparsity and Compressed Sensing 1
Praneeth Narayanamurthy · Namrata Vaswani
[ PDF]  [ Video] 
Oral
Wed Jul 11 04:50 AM -- 05:10 AM (PDT) @ A4
Bayesian Quadrature for Multiple Related Integrals
In Gaussian Processes 1
Xiaoyue Xi · Francois-Xavier Briol · Mark Girolami
[ PDF]  [ Video] 
Oral
Wed Jul 11 04:50 AM -- 05:10 AM (PDT) @ A6
Stability and Generalization of Learning Algorithms that Converge to Global Optima
In Statistical Learning Theory 2
Zachary Charles · Dimitris Papailiopoulos
[ PDF]  [ Video] 
Oral
Wed Jul 11 04:50 AM -- 05:00 AM (PDT) @ A1
Structured Evolution with Compact Architectures for Scalable Policy Optimization
In Reinforcement Learning 2
Krzysztof Choromanski · Mark Rowland · Vikas Sindhwani · Richard E Turner · Adrian Weller
[ PDF]  [ Video] 
Oral
Wed Jul 11 04:50 AM -- 05:10 AM (PDT) @ K1 + K2
Variance Regularized Counterfactual Risk Minimization via Variational Divergence Minimization
In Other Applications 1
Hang Wu · May Wang
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:00 AM -- 05:10 AM (PDT) @ A1
Spotlight: Optimizing Device Placement for Training Deep Neural Networks
In Reinforcement Learning 2
Yuanxiang Gao · Li Chen · Baochun Li
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:10 AM -- 05:20 AM (PDT) @ A7
Learning Steady-States of Iterative Algorithms over Graphs
In Representation Learning 2
Hanjun Dai · Zornitsa Kozareva · Bo Dai · Alex Smola · Le Song
[ PDF] 
Oral
Wed Jul 11 05:10 AM -- 05:20 AM (PDT) @ K11
Stochastic PCA with $\ell_2$ and $\ell_1$ Regularization
In Dimensionality Reduction 1
Poorya Mianjy · Raman Arora
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:10 AM -- 05:20 AM (PDT) @ Victoria
Conditional Neural Processes
In Deep Learning (Neural Network Architectures) 2
Marta Garnelo · Dan Rosenbaum · Chris Maddison · Tiago Ramalho · David Saxton · Murray Shanahan · Yee Teh · Danilo J. Rezende · S. M. Ali Eslami
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:10 AM -- 05:20 AM (PDT) @ K1 + K2
An Estimation and Analysis Framework for the Rasch Model
In Other Applications 1
Andrew Lan · Mung Chiang · Christoph Studer
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:10 AM -- 05:20 AM (PDT) @ A3
BOHB: Robust and Efficient Hyperparameter Optimization at Scale
In Optimization (Bayesian) 1
Stefan Falkner · Aaron Klein · Frank Hutter
[ PDF] 
Oral
Wed Jul 11 05:10 AM -- 05:20 AM (PDT) @ A9
Katyusha X: Simple Momentum Method for Stochastic Sum-of-Nonconvex Optimization
In Optimization (Non-convex) 1
Zeyuan Allen-Zhu
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:10 AM -- 05:20 AM (PDT) @ A4
Differentiable Compositional Kernel Learning for Gaussian Processes
In Gaussian Processes 1
Shengyang Sun · Guodong Zhang · Chaoqi Wang · Wenyuan Zeng · Jiaman Li · Roger Grosse
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:10 AM -- 05:20 AM (PDT) @ A1
Gated Path Planning Networks
In Reinforcement Learning 2
Lisa Lee · Emilio Parisotto · Devendra Singh Chaplot · Eric Xing · Ruslan Salakhutdinov
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:10 AM -- 05:20 AM (PDT) @ A5
Safe Element Screening for Submodular Function Minimization
In Sparsity and Compressed Sensing 1
Weizhong Zhang · Bin Hong · Lin Ma · Wei Liu · Tong Zhang
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:10 AM -- 05:20 AM (PDT) @ A6
Optimal Rates of Sketched-regularized Algorithms for Least-Squares Regression over Hilbert Spaces
In Statistical Learning Theory 2
Junhong Lin · Volkan Cevher
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:20 AM -- 05:30 AM (PDT) @ K11
Streaming Principal Component Analysis in Noisy Setting
In Dimensionality Reduction 1
Teodor Vanislavov Marinov · Poorya Mianjy · Raman Arora
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:20 AM -- 05:30 AM (PDT) @ A3
Bayesian Optimization of Combinatorial Structures
In Optimization (Bayesian) 1
Ricardo Baptista · Matthias Poloczek
[ PDF] 
Oral
Wed Jul 11 05:20 AM -- 05:30 AM (PDT) @ A1
Best Arm Identification in Linear Bandits with Linear Dimension Dependency
In Reinforcement Learning 2
Chao Tao · Saúl A. Blanco · Yuan Zhou
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:20 AM -- 05:30 AM (PDT) @ Victoria
A Semantic Loss Function for Deep Learning with Symbolic Knowledge
In Deep Learning (Neural Network Architectures) 2
Jingyi Xu · Zilu Zhang · Tal Friedman · Yitao Liang · Guy Van den Broeck
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:20 AM -- 05:30 AM (PDT) @ A9
$D^2$: Decentralized Training over Decentralized Data
In Optimization (Non-convex) 1
Hanlin Tang · Xiangru Lian · Ming Yan · Ce Zhang · Ji Liu
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:20 AM -- 05:30 AM (PDT) @ K1 + K2
End-to-end Active Object Tracking via Reinforcement Learning
In Other Applications 1
Wenhan Luo · Peng Sun · Fangwei Zhong · Wei Liu · Tong Zhang · Yizhou Wang
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:20 AM -- 05:30 AM (PDT) @ A6
Dropout Training, Data-dependent Regularization, and Generalization Bounds
In Statistical Learning Theory 2
Wenlong Mou · Yuchen Zhou · Jun Gao · Liwei Wang
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:20 AM -- 05:30 AM (PDT) @ A5
Online Convolutional Sparse Coding with Sample-Dependent Dictionary
In Sparsity and Compressed Sensing 1
Yaqing WANG · Quanming Yao · James Kwok · Lionel NI
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:20 AM -- 05:30 AM (PDT) @ A7
Anonymous Walk Embeddings
In Representation Learning 2
Sergey Ivanov · Evgeny Burnaev
[ PDF] 
Oral
Wed Jul 11 05:20 AM -- 05:30 AM (PDT) @ A4
Generalized Robust Bayesian Committee Machine for Large-scale Gaussian Process Regression
In Gaussian Processes 1
Haitao Liu · Jianfei Cai · Yi Wang · Yew Soon ONG
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:30 AM -- 05:50 AM (PDT) @ A7
Generative Temporal Models with Spatial Memory for Partially Observed Environments
In Representation Learning 3
Marco Fraccaro · Danilo J. Rezende · Yori Zwols · Alexander Pritzel · S. M. Ali Eslami · Fabio Viola
[ PDF] 
Oral
Wed Jul 11 05:30 AM -- 05:50 AM (PDT) @ A9
An Alternative View: When Does SGD Escape Local Minima?
In Optimization (Non-convex) 2
Bobby Kleinberg · Yuanzhi Li · Yang Yuan
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:30 AM -- 05:50 AM (PDT) @ A5
The Limits of Maxing, Ranking, and Preference Learning
In Ranking and Preference Learning 1
Moein Falahatgar · Ayush Jain · Alon Orlitsky · Venkatadheeraj Pichapati · Vaishakh Ravindrakumar
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:30 AM -- 05:50 AM (PDT) @ A1
Structured Control Nets for Deep Reinforcement Learning
In Reinforcement Learning 3
Mario Srouji · Jian Zhang · Ruslan Salakhutdinov
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:30 AM -- 05:50 AM (PDT) @ K11
Linear Spectral Estimators and an Application to Phase Retrieval
In Sparsity and Compressed Sensing 2
Ramina Ghods · Andrew Lan · Tom Goldstein · Christoph Studer
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:30 AM -- 05:50 AM (PDT) @ A3
Design of Experiments for Model Discrimination Hybridising Analytical and Data-Driven Approaches
In Active Learning 1
Simon Olofsson · Marc P Deisenroth · Ruth Misener
[ PDF] 
Oral
Wed Jul 11 05:30 AM -- 05:50 AM (PDT) @ A6
Information Theoretic Guarantees for Empirical Risk Minimization with Applications to Model Selection and Large-Scale Optimization
In Statistical Learning Theory 3
Ibrahim Alabdulmohsin
[ PDF] 
Oral
Wed Jul 11 05:30 AM -- 05:50 AM (PDT) @ K1 + K2
Deep Predictive Coding Network for Object Recognition
In Computer Vision 1
Haiguang Wen · Kuan Han · Junxing Shi · Yizhen Zhang · Eugenio Culurciello · Zhongming Liu
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:30 AM -- 05:50 AM (PDT) @ A4
Variational Inference and Model Selection with Generalized Evidence Bounds
In Deep Learning (Bayesian) 1
Liqun Chen · Chenyang Tao · RUIYI (ROY) ZHANG · Ricardo Henao · Lawrence Carin
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:30 AM -- 05:50 AM (PDT) @ Victoria
Non-linear motor control by local learning in spiking neural networks
In Deep Learning (Neural Network Architectures) 3
Aditya Gilra · Wulfram Gerstner
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:50 AM -- 06:00 AM (PDT) @ A6
The Generalization Error of Dictionary Learning with Moreau Envelopes
In Statistical Learning Theory 3
ALEXANDROS GEORGOGIANNIS
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:50 AM -- 06:00 AM (PDT) @ A5
Learning a Mixture of Two Multinomial Logits
In Ranking and Preference Learning 1
Flavio Chierichetti · Ravi Kumar · Andrew Tomkins
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:50 AM -- 06:10 AM (PDT) @ A9
Escaping Saddles with Stochastic Gradients
In Optimization (Non-convex) 2
Hadi Daneshmand · Jonas Kohler · Aurelien Lucchi · Thomas Hofmann
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:50 AM -- 06:00 AM (PDT) @ K1 + K2
Gradually Updated Neural Networks for Large-Scale Image Recognition
In Computer Vision 1
Siyuan Qiao · Zhishuai Zhang · Wei Shen · Bo Wang · Alan Yuille
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:50 AM -- 06:10 AM (PDT) @ K11
Covariate Adjusted Precision Matrix Estimation via Nonconvex Optimization
In Sparsity and Compressed Sensing 2
Jinghui Chen · Pan Xu · Lingxiao Wang · Jian Ma · Quanquan Gu
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:50 AM -- 06:10 AM (PDT) @ A1
Latent Space Policies for Hierarchical Reinforcement Learning
In Reinforcement Learning 3
Tuomas Haarnoja · Kristian Hartikainen · Pieter Abbeel · Sergey Levine
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:50 AM -- 06:10 AM (PDT) @ A4
Fixing a Broken ELBO
In Deep Learning (Bayesian) 1
Alexander Alemi · Ben Poole · Ian Fischer · Joshua V Dillon · Rif Saurous · Kevin Murphy
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:50 AM -- 06:00 AM (PDT) @ A7
Disentangling by Factorising
In Representation Learning 3
Hyunjik Kim · Andriy Mnih
[ PDF] 
Oral
Wed Jul 11 05:50 AM -- 06:00 AM (PDT) @ Victoria
PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learning
In Deep Learning (Neural Network Architectures) 3
Yunbo Wang · Zhifeng Gao · Mingsheng Long · Jianmin Wang · Philip Yu
[ PDF]  [ Video] 
Oral
Wed Jul 11 05:50 AM -- 06:10 AM (PDT) @ A3
Selecting Representative Examples for Program Synthesis
In Active Learning 1
Yewen Pu · Zachery Miranda · Armando Solar-Lezama · Leslie Kaelbling
[ PDF] 
Oral
Wed Jul 11 06:00 AM -- 06:10 AM (PDT) @ A6
On Learning Sparsely Used Dictionaries from Incomplete Samples
In Statistical Learning Theory 3
Thanh Nguyen · Akshay Soni · Chinmay Hegde
[ PDF]  [ Video] 
Oral
Wed Jul 11 06:00 AM -- 06:10 AM (PDT) @ A5
The Weighted Kendall and High-order Kernels for Permutations
In Ranking and Preference Learning 1
Yunlong Jiao · Jean-Philippe Vert
[ PDF]  [ Video] 
Oral
Wed Jul 11 06:00 AM -- 06:10 AM (PDT) @ K1 + K2
Neural Inverse Rendering for General Reflectance Photometric Stereo
In Computer Vision 1
Tatsunori Taniai · Takanori Maehara
[ PDF]  [ Video] 
Oral
Wed Jul 11 06:00 AM -- 06:10 AM (PDT) @ A7
Discovering Interpretable Representations for Both Deep Generative and Discriminative Models
In Representation Learning 3
Tameem Adel · Zoubin Ghahramani · Adrian Weller
[ PDF] 
Oral
Wed Jul 11 06:00 AM -- 06:10 AM (PDT) @ Victoria
Hierarchical Long-term Video Prediction without Supervision
In Deep Learning (Neural Network Architectures) 3
Nevan Wichers · Ruben Villegas · Dumitru Erhan · Honglak Lee
[ PDF]  [ Video] 
Oral
Wed Jul 11 06:10 AM -- 06:20 AM (PDT) @ K1 + K2
One-Shot Segmentation in Clutter
In Computer Vision 1
Claudio Michaelis · Matthias Bethge · Alexander Ecker
[ PDF]  [ Video] 
Oral
Wed Jul 11 06:10 AM -- 06:20 AM (PDT) @ A9
Stochastic Variance-Reduced Cubic Regularized Newton Method
In Optimization (Non-convex) 2
Dongruo Zhou · Pan Xu · Quanquan Gu
[ PDF]  [ Video] 
Oral
Wed Jul 11 06:10 AM -- 06:20 AM (PDT) @ K11
Signal and Noise Statistics Oblivious Orthogonal Matching Pursuit
In Sparsity and Compressed Sensing 2
Sreejith Kallummil · Sheetal Kalyani
[ PDF]  [ Video] 
Oral
Wed Jul 11 06:10 AM -- 06:20 AM (PDT) @ Victoria
Exploiting the Potential of Standard Convolutional Autoencoders for Image Restoration by Evolutionary Search
In Deep Learning (Neural Network Architectures) 3
Masanori SUGANUMA · Mete Ozay · Takayuki Okatani
[ PDF]  [ Video] 
Oral
Wed Jul 11 06:10 AM -- 06:20 AM (PDT) @ A3
On the Relationship between Data Efficiency and Error for Uncertainty Sampling
In Active Learning 1
Stephen Mussmann · Percy Liang
[ PDF] 
Oral
Wed Jul 11 06:10 AM -- 06:20 AM (PDT) @ A7
Learning Independent Causal Mechanisms
In Representation Learning 3
Giambattista Parascandolo · Niki Kilbertus · Mateo Rojas-Carulla · Bernhard Schölkopf
[ PDF] 
Oral
Wed Jul 11 06:10 AM -- 06:20 AM (PDT) @ A6
The Well-Tempered Lasso
In Statistical Learning Theory 3
Yuanzhi Li · Yoram Singer
[ PDF]  [ Video] 
Oral
Wed Jul 11 06:10 AM -- 06:20 AM (PDT) @ A5
Parameterized Algorithms for the Matrix Completion Problem
In Ranking and Preference Learning 1
Robert Ganian · DePaul Iyad Kanj · Sebastian Ordyniak · Stefan Szeider
[ PDF]  [ Video] 
Oral
Wed Jul 11 06:10 AM -- 06:20 AM (PDT) @ A4
Tighter Variational Bounds are Not Necessarily Better
In Deep Learning (Bayesian) 1
Tom Rainforth · Adam Kosiorek · Tuan Anh Le · Chris Maddison · Maximilian Igl · Frank Wood · Yee-Whye Teh
[ PDF]  [ Video] 
Oral
Wed Jul 11 06:10 AM -- 06:20 AM (PDT) @ A1
Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory Embeddings
In Reinforcement Learning 3
John Co-Reyes · Yu Xuan Liu · Abhishek Gupta · Benjamin Eysenbach · Pieter Abbeel · Sergey Levine
[ PDF]  [ Video] 
Oral
Wed Jul 11 06:20 AM -- 06:30 AM (PDT) @ K1 + K2
Active Testing: An Efficient and Robust Framework for Estimating Accuracy
In Computer Vision 1
Phuc Nguyen · Deva Ramanan · Charless Fowlkes
[ PDF]  [ Video] 
Oral
Wed Jul 11 06:20 AM -- 06:30 AM (PDT) @ A4
Continuous-Time Flows for Efficient Inference and Density Estimation
In Deep Learning (Bayesian) 1
Changyou Chen · Chunyuan Li · Liquan Chen · Wenlin Wang · Yunchen Pu · Lawrence Carin
[ PDF]  [ Video] 
Oral
Wed Jul 11 06:20 AM -- 06:30 AM (PDT) @ Victoria
Model-Level Dual Learning
In Deep Learning (Neural Network Architectures) 3
Yingce Xia · Xu Tan · Fei Tian · Tao Qin · Nenghai Yu · Tie-Yan Liu
[ PDF]  [ Video] 
Oral
Wed Jul 11 06:20 AM -- 06:30 AM (PDT) @ A6
Differentially Private Identity and Equivalence Testing of Discrete Distributions
In Statistical Learning Theory 3
Maryam Aliakbarpour · Ilias Diakonikolas · MIT Ronitt Rubinfeld
[ PDF]  [ Video] 
Oral
Wed Jul 11 06:20 AM -- 06:30 AM (PDT) @ A1
An Inference-Based Policy Gradient Method for Learning Options
In Reinforcement Learning 3
Matthew Smith · Herke van Hoof · Joelle Pineau
[ PDF]  [ Video] 
Oral
Wed Jul 11 06:20 AM -- 06:30 AM (PDT) @ A7
Contextual Graph Markov Model: A Deep and Generative Approach to Graph Processing
In Representation Learning 3
Davide Bacciu · Federico Errica · Alessio Micheli
[ PDF] 
Oral
Wed Jul 11 06:20 AM -- 06:30 AM (PDT) @ A9
Non-convex Conditional Gradient Sliding
In Optimization (Non-convex) 2
chao qu · Yan Li · Huan Xu
[ PDF]  [ Video] 
Oral
Wed Jul 11 06:20 AM -- 06:30 AM (PDT) @ K11
Testing Sparsity over Known and Unknown Bases
In Sparsity and Compressed Sensing 2
Siddharth Barman · Arnab Bhattacharyya · Suprovat Ghoshal
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:00 AM -- 07:20 AM (PDT) @ A4
Semi-Implicit Variational Inference
In Approximate Inference 1
Mingzhang Yin · Mingyuan Zhou
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:00 AM -- 07:20 AM (PDT) @ A1
Programmatically Interpretable Reinforcement Learning
In Reinforcement Learning 4
Abhinav Verma · Vijayaraghavan Murali · Rishabh Singh · Pushmeet Kohli · Swarat Chaudhuri
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:00 AM -- 07:20 AM (PDT) @ A7
Which Training Methods for GANs do actually Converge?
In Generative Models 1
Lars Mescheder · Andreas Geiger · Sebastian Nowozin
[ PDF] 
Oral
Wed Jul 11 07:00 AM -- 07:20 AM (PDT) @ Victoria
Adafactor: Adaptive Learning Rates with Sublinear Memory Cost
In Deep Learning (Neural Network Architectures) 4
Noam Shazeer · Mitchell Stern
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:00 AM -- 07:20 AM (PDT) @ A6
Differentially Private Matrix Completion Revisited
In Privacy, Anonymity, and Security 1
Prateek Jain · Om Dipakbhai Thakkar · Abhradeep Thakurta
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:00 AM -- 07:20 AM (PDT) @ K1 + K2
Dynamical Isometry and a Mean Field Theory of CNNs: How to Train 10,000-Layer Vanilla Convolutional Neural Networks
In Deep Learning (Theory) 1
Lechao Xiao · Yasaman Bahri · Jascha Sohl-Dickstein · Samuel Schoenholz · Jeffrey Pennington
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:00 AM -- 07:20 AM (PDT) @ A5
Stochastic Training of Graph Convolutional Networks with Variance Reduction
In Networks and Relational Learning 1
Jianfei Chen · Jun Zhu · Le Song
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:00 AM -- 07:20 AM (PDT) @ A9
Dissipativity Theory for Accelerating Stochastic Variance Reduction: A Unified Analysis of SVRG and Katyusha Using Semidefinite Programs
In Optimization (Convex) 1
Bin Hu · Stephen Wright · Laurent Lessard
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:00 AM -- 07:20 AM (PDT) @ A3
Competitive Multi-agent Inverse Reinforcement Learning with Sub-optimal Demonstrations
In Reinforcement Learning 5
IEMS Xingyu Wang · Diego Klabjan
[ PDF] 
Oral
Wed Jul 11 07:00 AM -- 07:20 AM (PDT) @ K11
Weakly Submodular Maximization Beyond Cardinality Constraints: Does Randomization Help Greedy?
In Optimization (Combinatorial) 1
Lin Chen · Moran Feldman · Amin Karbasi
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:20 AM -- 07:40 AM (PDT) @ A5
Representation Learning on Graphs with Jumping Knowledge Networks
In Networks and Relational Learning 1
Keyulu Xu · Chengtao Li · Yonglong Tian · Tomohiro Sonobe · Ken-ichi Kawarabayashi · Stefanie Jegelka
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:20 AM -- 07:40 AM (PDT) @ A4
Efficient Gradient-Free Variational Inference using Policy Search
In Approximate Inference 1
Oleg Arenz · Gerhard Neumann · Mingjun Zhong
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:20 AM -- 07:40 AM (PDT) @ K11
Beyond 1/2-Approximation for Submodular Maximization on Massive Data Streams
In Optimization (Combinatorial) 1
Ashkan Norouzi-Fard · Jakub Tarnawski · Slobodan Mitrovic · Amir Zandieh · Aidasadat Mousavifar · Ola Svensson
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:20 AM -- 07:40 AM (PDT) @ A1
Learning by Playing - Solving Sparse Reward Tasks from Scratch
In Reinforcement Learning 4
Martin Riedmiller · Roland Hafner · Thomas Lampe · Michael Neunert · Jonas Degrave · Tom Van de Wiele · Vlad Mnih · Nicolas Heess · Jost Springenberg
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:20 AM -- 07:40 AM (PDT) @ A3
Feedback-Based Tree Search for Reinforcement Learning
In Reinforcement Learning 5
Daniel Jiang · Emmanuel Ekwedike · Han Liu
[ PDF] 
Oral
Wed Jul 11 07:20 AM -- 07:30 AM (PDT) @ A9
Lyapunov Functions for First-Order Methods: Tight Automated Convergence Guarantees
In Optimization (Convex) 1
Adrien Taylor · Bryan Van Scoy · Laurent Lessard
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:20 AM -- 07:40 AM (PDT) @ K1 + K2
The Dynamics of Learning: A Random Matrix Approach
In Deep Learning (Theory) 1
Zhenyu Liao · Romain Couillet
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:20 AM -- 07:40 AM (PDT) @ A7
Chi-square Generative Adversarial Network
In Generative Models 1
Chenyang Tao · Liqun Chen · Ricardo Henao · Jianfeng Feng · Lawrence Carin
[ PDF] 
Oral
Wed Jul 11 07:20 AM -- 07:30 AM (PDT) @ Victoria
Orthogonal Recurrent Neural Networks with Scaled Cayley Transform
In Deep Learning (Neural Network Architectures) 4
Kyle Helfrich · Devin Willmott · Qiang Ye
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:20 AM -- 07:30 AM (PDT) @ A6
Mitigating Bias in Adaptive Data Gathering via Differential Privacy
In Privacy, Anonymity, and Security 1
Seth Neel · Aaron Roth
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:30 AM -- 07:40 AM (PDT) @ A9
ADMM and Accelerated ADMM as Continuous Dynamical Systems
In Optimization (Convex) 1
Guilherme Franca · Daniel Robinson · Rene Vidal
[ PDF] 
Oral
Wed Jul 11 07:30 AM -- 07:40 AM (PDT) @ A6
Local Private Hypothesis Testing: Chi-Square Tests
In Privacy, Anonymity, and Security 1
Marco Gaboardi · Ryan Rogers
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:30 AM -- 07:40 AM (PDT) @ Victoria
Kronecker Recurrent Units
In Deep Learning (Neural Network Architectures) 4
Cijo Jose · Mouhamadou Moustapha Cisse · Francois Fleuret
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:40 AM -- 07:50 AM (PDT) @ K11
Scalable Deletion-Robust Submodular Maximization: Data Summarization with Privacy and Fairness Constraints
In Optimization (Combinatorial) 1
Ehsan Kazemi · Morteza Zadimoghaddam · Amin Karbasi
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:40 AM -- 07:50 AM (PDT) @ A5
Learning Diffusion using Hyperparameters
In Networks and Relational Learning 1
Dimitrios Kalimeris · Yaron Singer · Karthik Subbian · Udi Weinsberg
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:40 AM -- 07:50 AM (PDT) @ A1
Automatic Goal Generation for Reinforcement Learning Agents
In Reinforcement Learning 4
Carlos Florensa · David Held · Xinyang Geng · Pieter Abbeel
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:40 AM -- 07:50 AM (PDT) @ A6
Locally Private Hypothesis Testing
In Privacy, Anonymity, and Security 1
Or Sheffet
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:40 AM -- 07:50 AM (PDT) @ Victoria
Fast Parametric Learning with Activation Memorization
In Deep Learning (Neural Network Architectures) 4
Jack Rae · Chris Dyer · Peter Dayan · Timothy Lillicrap
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:40 AM -- 07:50 AM (PDT) @ K1 + K2
On the Optimization of Deep Networks: Implicit Acceleration by Overparameterization
In Deep Learning (Theory) 1
Sanjeev Arora · Nadav Cohen · Elad Hazan
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:40 AM -- 07:50 AM (PDT) @ A7
Learning Implicit Generative Models with the Method of Learned Moments
In Generative Models 1
Suman Ravuri · Shakir Mohamed · Mihaela Rosca · Oriol Vinyals
[ PDF] 
Oral
Wed Jul 11 07:40 AM -- 07:50 AM (PDT) @ A3
Deep Reinforcement Learning in Continuous Action Spaces: a Case Study in the Game of Simulated Curling
In Reinforcement Learning 5
kyowoon Lee · Sol-A Kim · Jaesik Choi · Seong-Whan Lee
[ PDF] 
Oral
Wed Jul 11 07:40 AM -- 07:50 AM (PDT) @ A9
Computational Optimal Transport: Complexity by Accelerated Gradient Descent Is Better Than by Sinkhorn's Algorithm
In Optimization (Convex) 1
Pavel Dvurechenskii · Alexander Gasnikov · Alexey Kroshnin
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:40 AM -- 07:50 AM (PDT) @ A4
A Spectral Approach to Gradient Estimation for Implicit Distributions
In Approximate Inference 1
Jiaxin Shi · Shengyang Sun · Jun Zhu
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:50 AM -- 08:00 AM (PDT) @ A9
An Efficient Semismooth Newton based Algorithm for Convex Clustering
In Optimization (Convex) 1
Yancheng Yuan · Defeng Sun · Kim-Chuan Toh
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:50 AM -- 08:00 AM (PDT) @ A5
Canonical Tensor Decomposition for Knowledge Base Completion
In Networks and Relational Learning 1
Timothee Lacroix · Nicolas Usunier · Guillaume Obozinski
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:50 AM -- 08:00 AM (PDT) @ A3
Learning the Reward Function for a Misspecified Model
In Reinforcement Learning 5
Erik Talvitie
[ PDF] 
Oral
Wed Jul 11 07:50 AM -- 08:00 AM (PDT) @ Victoria
Dynamic Evaluation of Neural Sequence Models
In Deep Learning (Neural Network Architectures) 4
Ben Krause · Emmanuel Kahembwe · Iain Murray · Steve Renals
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:50 AM -- 08:00 AM (PDT) @ K1 + K2
Deep Linear Networks with Arbitrary Loss: All Local Minima Are Global
In Deep Learning (Theory) 1
Thomas Laurent · James von Brecht
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:50 AM -- 08:00 AM (PDT) @ K11
Data Summarization at Scale: A Two-Stage Submodular Approach
In Optimization (Combinatorial) 1
Marko Mitrovic · Ehsan Kazemi · Morteza Zadimoghaddam · Amin Karbasi
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:50 AM -- 08:00 AM (PDT) @ A6
INSPECTRE: Privately Estimating the Unseen
In Privacy, Anonymity, and Security 1
Jayadev Acharya · Gautam Kamath · Ziteng Sun · Huanyu Zhang
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:50 AM -- 08:00 AM (PDT) @ A7
A Classification-Based Study of Covariate Shift in GAN Distributions
In Generative Models 1
Shibani Santurkar · Ludwig Schmidt · Aleksander Madry
[ PDF] 
Oral
Wed Jul 11 07:50 AM -- 08:00 AM (PDT) @ A1
Universal Planning Networks: Learning Generalizable Representations for Visuomotor Control
In Reinforcement Learning 4
Aravind Srinivas · Allan Jabri · Pieter Abbeel · Sergey Levine · Chelsea Finn
[ PDF]  [ Video] 
Oral
Wed Jul 11 07:50 AM -- 08:00 AM (PDT) @ A4
Quasi-Monte Carlo Variational Inference
In Approximate Inference 1
Alexander Buchholz · Florian Wenzel · Stephan Mandt
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:00 AM -- 08:20 AM (PDT) @ A3
Machine Theory of Mind
In Reinforcement Learning 7
Neil Rabinowitz · Frank Perbet · Francis Song · Chiyuan Zhang · S. M. Ali Eslami · Matthew Botvinick
[ PDF] 
Oral
Wed Jul 11 08:00 AM -- 08:20 AM (PDT) @ A4
Yes, but Did It Work?: Evaluating Variational Inference
In Approximate Inference 2
Yuling Yao · Aki Vehtari · Daniel Simpson · Andrew Gelman
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:00 AM -- 08:20 AM (PDT) @ A5
Dependent Relational Gamma Process Models for Longitudinal Networks
In Networks and Relational Learning 2
Sikun Yang · Heinz Koeppl
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:00 AM -- 08:20 AM (PDT) @ K11
Learning to Optimize Combinatorial Functions
In Optimization (Combinatorial) 2
Nir Rosenfeld · Eric Balkanski · Amir Globerson · Yaron Singer
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:00 AM -- 08:20 AM (PDT) @ A6
Delayed Impact of Fair Machine Learning
In Society Impacts of Machine Learning 1
Lydia T. Liu · Sarah Dean · Esther Rolf · Max Simchowitz · Moritz Hardt
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:00 AM -- 08:20 AM (PDT) @ Victoria
Decoupled Parallel Backpropagation with Convergence Guarantee
In Deep Learning (Neural Network Architectures) 5
Zhouyuan Huo · Bin Gu · Qian Yang · Heng Huang
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:00 AM -- 08:20 AM (PDT) @ A1
Efficient Bias-Span-Constrained Exploration-Exploitation in Reinforcement Learning
In Reinforcement Learning 6
Ronan Fruit · Matteo Pirotta · Alessandro Lazaric · Ronald Ortner
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:00 AM -- 08:20 AM (PDT) @ K1 + K2
Essentially No Barriers in Neural Network Energy Landscape
In Deep Learning (Theory) 2
Felix Draxler · Kambis Veschgini · Manfred Salmhofer · Fred Hamprecht
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:00 AM -- 08:20 AM (PDT) @ A7
Differentiable Abstract Interpretation for Provably Robust Neural Networks
In Deep Learning (Adversarial) 1
Matthew Mirman · Timon Gehr · Martin Vechev
[ PDF] 
Oral
Wed Jul 11 08:00 AM -- 08:20 AM (PDT) @ A9
The Power of Interpolation: Understanding the Effectiveness of SGD in Modern Over-parametrized Learning
In Optimization (Convex) 2
Siyuan Ma · Raef Bassily · Mikhail Belkin
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:20 AM -- 08:30 AM (PDT) @ K1 + K2
Comparing Dynamics: Deep Neural Networks versus Glassy Systems
In Deep Learning (Theory) 2
Marco Baity-Jesi · Levent Sagun · Mario Geiger · Stefano Spigler · Gerard Arous · Chiara Cammarota · Yann LeCun · Matthieu Wyart · Giulio Biroli
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:20 AM -- 08:40 AM (PDT) @ A6
Fairness Without Demographics in Repeated Loss Minimization
In Society Impacts of Machine Learning 1
Tatsunori Hashimoto · Megha Srivastava · Hongseok Namkoong · Percy Liang
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:20 AM -- 08:30 AM (PDT) @ A9
Fast Variance Reduction Method with Stochastic Batch Size
In Optimization (Convex) 2
University of California Xuanqing Liu · Cho-Jui Hsieh
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:20 AM -- 08:40 AM (PDT) @ A1
Path Consistency Learning in Tsallis Entropy Regularized MDPs
In Reinforcement Learning 6
Yinlam Chow · Ofir Nachum · Mohammad Ghavamzadeh
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:20 AM -- 08:40 AM (PDT) @ Victoria
Efficient Neural Architecture Search via Parameters Sharing
In Deep Learning (Neural Network Architectures) 5
Hieu Pham · Melody Guan · Barret Zoph · Quoc Le · Jeff Dean
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:20 AM -- 08:40 AM (PDT) @ A3
Transfer in Deep Reinforcement Learning Using Successor Features and Generalised Policy Improvement
In Reinforcement Learning 7
Andre Barreto · Diana Borsa · John Quan · Tom Schaul · David Silver · Matteo Hessel · Daniel J. Mankowitz · Augustin Zidek · Remi Munos
[ PDF] 
Oral
Wed Jul 11 08:20 AM -- 08:40 AM (PDT) @ A4
Augment and Reduce: Stochastic Inference for Large Categorical Distributions
In Approximate Inference 2
Francisco Ruiz · Michalis Titsias · Adji Bousso Dieng · David Blei
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:20 AM -- 08:30 AM (PDT) @ K11
Proportional Allocation: Simple, Distributed, and Diverse Matching with High Entropy
In Optimization (Combinatorial) 2
Shipra Agarwal · Morteza Zadimoghaddam · Vahab Mirrokni
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:20 AM -- 08:40 AM (PDT) @ A5
NetGAN: Generating Graphs via Random Walks
In Networks and Relational Learning 2
Aleksandar Bojchevski · Oleksandr Shchur · Daniel Zügner · Stephan Günnemann
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:20 AM -- 08:40 AM (PDT) @ A7
Provable Defenses against Adversarial Examples via the Convex Outer Adversarial Polytope
In Deep Learning (Adversarial) 1
Eric Wong · Zico Kolter
[ PDF] 
Oral
Wed Jul 11 08:30 AM -- 08:40 AM (PDT) @ K1 + K2
Not All Samples Are Created Equal: Deep Learning with Importance Sampling
In Deep Learning (Theory) 2
Angelos Katharopoulos · Francois Fleuret
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:30 AM -- 08:40 AM (PDT) @ K11
Binary Partitions with Approximate Minimum Impurity
In Optimization (Combinatorial) 2
Eduardo Laber · Marco Molinaro · Felipe de A. Mello Pereira
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:30 AM -- 08:40 AM (PDT) @ A9
SGD and Hogwild! Convergence Without the Bounded Gradients Assumption
In Optimization (Convex) 2
Lam Nguyen · PHUONG_HA NGUYEN · Marten van Dijk · Peter Richtarik · Katya Scheinberg · Martin Takac
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:40 AM -- 08:50 AM (PDT) @ A4
Black-Box Variational Inference for Stochastic Differential Equations
In Approximate Inference 2
Tom Ryder · Andrew Golightly · Stephen McGough · Dennis Prangle
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:40 AM -- 08:50 AM (PDT) @ A6
Nonconvex Optimization for Regression with Fairness Constraints
In Society Impacts of Machine Learning 1
Junpei Komiyama · Akiko Takeda · Junya Honda · Hajime Shimao
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:40 AM -- 08:50 AM (PDT) @ A1
Improved Regret Bounds for Thompson Sampling in Linear Quadratic Control Problems
In Reinforcement Learning 6
Marc Abeille · Alessandro Lazaric
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:40 AM -- 08:50 AM (PDT) @ A9
Lightweight Stochastic Optimization for Minimizing Finite Sums with Infinite Data
In Optimization (Convex) 2
Shuai Zheng · James Kwok
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:40 AM -- 08:50 AM (PDT) @ K11
Partial Optimality and Fast Lower Bounds for Weighted Correlation Clustering
In Optimization (Combinatorial) 2
Jan-Hendrik Lange · Andreas Karrenbauer · Bjoern Andres
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:40 AM -- 08:50 AM (PDT) @ A7
Synthesizing Robust Adversarial Examples
In Deep Learning (Adversarial) 1
Anish Athalye · Logan Engstrom · Andrew Ilyas · Kevin Kwok
[ PDF] 
Oral
Wed Jul 11 08:40 AM -- 08:50 AM (PDT) @ A5
GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models
In Networks and Relational Learning 2
Jiaxuan You · Rex (Zhitao) Ying · Xiang Ren · Will Hamilton · Jure Leskovec
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:40 AM -- 08:50 AM (PDT) @ Victoria
Stabilizing Gradients for Deep Neural Networks via Efficient SVD Parameterization
In Deep Learning (Neural Network Architectures) 5
Jiong Zhang · Qi Lei · Inderjit Dhillon
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:40 AM -- 08:50 AM (PDT) @ K1 + K2
Learning Deep ResNet Blocks Sequentially using Boosting Theory
In Deep Learning (Theory) 2
Furong Huang · Jordan Ash · John Langford · Robert Schapire
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:40 AM -- 08:50 AM (PDT) @ A3
Been There, Done That: Meta-Learning with Episodic Recall
In Reinforcement Learning 7
Samuel Ritter · Jane Wang · Zeb Kurth-Nelson · Siddhant Jayakumar · Charles Blundell · Razvan Pascanu · Matthew Botvinick
[ PDF] 
Oral
Wed Jul 11 08:50 AM -- 09:00 AM (PDT) @ A5
Neural Relational Inference for Interacting Systems
In Networks and Relational Learning 2
Thomas Kipf · Ethan Fetaya · Kuan-Chieh Wang · Max Welling · Richard Zemel
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:50 AM -- 09:00 AM (PDT) @ K11
Bounds on the Approximation Power of Feedforward Neural Networks
In Optimization (Combinatorial) 2
Mohammad Mehrabi · Aslan Tchamkerten · MANSOOR I YOUSEFI
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:50 AM -- 09:00 AM (PDT) @ A4
Inference Suboptimality in Variational Autoencoders
In Approximate Inference 2
Chris Cremer · Xuechen Li · David Duvenaud
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:50 AM -- 09:00 AM (PDT) @ A7
Adversarial Risk and the Dangers of Evaluating Against Weak Attacks
In Deep Learning (Adversarial) 1
Jonathan Uesato · Brendan O'Donoghue · Pushmeet Kohli · Aäron van den Oord
[ PDF] 
Oral
Wed Jul 11 08:50 AM -- 09:00 AM (PDT) @ K1 + K2
An Optimal Control Approach to Deep Learning and Applications to Discrete-Weight Neural Networks
In Deep Learning (Theory) 2
Qianxiao Li · IHPC Shuji Hao
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:50 AM -- 09:00 AM (PDT) @ A3
Continual Reinforcement Learning with Complex Synapses
In Reinforcement Learning 7
Christos Kaplanis · Murray Shanahan · Claudia Clopath
[ PDF] 
Oral
Wed Jul 11 08:50 AM -- 09:00 AM (PDT) @ A9
A Simple Stochastic Variance Reduced Algorithm with Fast Convergence Rates
In Optimization (Convex) 2
Kaiwen Zhou · Fanhua Shang · James Cheng
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:50 AM -- 09:00 AM (PDT) @ Victoria
Spline Filters For End-to-End Deep Learning
In Deep Learning (Neural Network Architectures) 5
Randall Balestriero · Romain Cosentino · Herve Glotin · Richard Baraniuk
[ PDF] 
Oral
Wed Jul 11 08:50 AM -- 09:00 AM (PDT) @ A6
Fair and Diverse DPP-Based Data Summarization
In Society Impacts of Machine Learning 1
L. Elisa Celis · Vijay Keswani · Damian Straszak · Amit Jayant Deshpande · Tarun Kathuria · Nisheeth Vishnoi
[ PDF]  [ Video] 
Oral
Wed Jul 11 08:50 AM -- 09:00 AM (PDT) @ A1
Least-Squares Temporal Difference Learning for the Linear Quadratic Regulator
In Reinforcement Learning 6
Stephen Tu · Benjamin Recht
[ PDF]  [ Video] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #1
Spline Filters For End-to-End Deep Learning
In Posters Wed
Randall Balestriero · Romain Cosentino · Herve Glotin · Richard Baraniuk
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #2
Non-linear motor control by local learning in spiking neural networks
In Posters Wed
Aditya Gilra · Wulfram Gerstner
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #3
Implicit Quantile Networks for Distributional Reinforcement Learning
In Posters Wed
Will Dabney · Georg Ostrovski · David Silver · Remi Munos
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #4
An Inference-Based Policy Gradient Method for Learning Options
In Posters Wed
Matthew Smith · Herke van Hoof · Joelle Pineau
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #5
Predict and Constrain: Modeling Cardinality in Deep Structured Prediction
In Posters Wed
Nataly Brukhim · Amir Globerson
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #6
Differentially Private Matrix Completion Revisited
In Posters Wed
Prateek Jain · Om Dipakbhai Thakkar · Abhradeep Thakurta
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #7
Differentiable plasticity: training plastic neural networks with backpropagation
In Posters Wed
Thomas Miconi · Kenneth Stanley · Jeff Clune
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #8
Model-Level Dual Learning
In Posters Wed
Yingce Xia · Xu Tan · Fei Tian · Tao Qin · Nenghai Yu · Tie-Yan Liu
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #9
CoVeR: Learning Covariate-Specific Vector Representations with Tensor Decompositions
In Posters Wed
Kevin Tian · Teng Zhang · James Zou
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #10
Tree Edit Distance Learning via Adaptive Symbol Embeddings
In Posters Wed
Benjamin Paaßen · Claudio Gallicchio · Alessio Micheli · CITEC Barbara Hammer
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #11
Gradually Updated Neural Networks for Large-Scale Image Recognition
In Posters Wed
Siyuan Qiao · Zhishuai Zhang · Wei Shen · Bo Wang · Alan Yuille
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #12
One-Shot Segmentation in Clutter
In Posters Wed
Claudio Michaelis · Matthias Bethge · Alexander Ecker
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #13
Active Testing: An Efficient and Robust Framework for Estimating Accuracy
In Posters Wed
Phuc Nguyen · Deva Ramanan · Charless Fowlkes
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #14
Learning Deep ResNet Blocks Sequentially using Boosting Theory
In Posters Wed
Furong Huang · Jordan Ash · John Langford · Robert Schapire
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #15
Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory Embeddings
In Posters Wed
John Co-Reyes · Yu Xuan Liu · Abhishek Gupta · Benjamin Eysenbach · Pieter Abbeel · Sergey Levine
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #16
Problem Dependent Reinforcement Learning Bounds Which Can Identify Bandit Structure in MDPs
In Posters Wed
Andrea Zanette · Emma Brunskill
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #17
Stochastic PCA with $\ell_2$ and $\ell_1$ Regularization
In Posters Wed
Poorya Mianjy · Raman Arora
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #18
Subspace Embedding and Linear Regression with Orlicz Norm
In Posters Wed
Alexandr Andoni · Chengyu Lin · Ying Sheng · Peilin Zhong · Ruiqi Zhong
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #19
Signal and Noise Statistics Oblivious Orthogonal Matching Pursuit
In Posters Wed
Sreejith Kallummil · Sheetal Kalyani
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #20
Provable Defenses against Adversarial Examples via the Convex Outer Adversarial Polytope
In Posters Wed
Eric Wong · Zico Kolter
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #21
Learning the Reward Function for a Misspecified Model
In Posters Wed
Erik Talvitie
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #22
Deep Reinforcement Learning in Continuous Action Spaces: a Case Study in the Game of Simulated Curling
In Posters Wed
kyowoon Lee · Sol-A Kim · Jaesik Choi · Seong-Whan Lee
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #23
Do Outliers Ruin Collaboration?
In Posters Wed
Mingda Qiao
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #24
Dropout Training, Data-dependent Regularization, and Generalization Bounds
In Posters Wed
Wenlong Mou · Yuchen Zhou · Jun Gao · Liwei Wang
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #25
Competitive Multi-agent Inverse Reinforcement Learning with Sub-optimal Demonstrations
In Posters Wed
IEMS Xingyu Wang · Diego Klabjan
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #26
Continual Reinforcement Learning with Complex Synapses
In Posters Wed
Christos Kaplanis · Murray Shanahan · Claudia Clopath
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #27
Equivalence of Multicategory SVM and Simplex Cone SVM: Fast Computations and Statistical Theory
In Posters Wed
Guillaume Pouliot
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #28
Quickshift++: Provably Good Initializations for Sample-Based Mean Shift
In Posters Wed
Heinrich Jiang · Jennifer Jang · Samory Kpotufe
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #29
Learning Diffusion using Hyperparameters
In Posters Wed
Dimitrios Kalimeris · Yaron Singer · Karthik Subbian · Udi Weinsberg
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #30
Learning a Mixture of Two Multinomial Logits
In Posters Wed
Flavio Chierichetti · Ravi Kumar · Andrew Tomkins
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #31
Crowdsourcing with Arbitrary Adversaries
In Posters Wed
Matthäus Kleindessner · Pranjal Awasthi
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #32
Deep Density Destructors
In Posters Wed
David Inouye · Pradeep Ravikumar
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #33
Programmatically Interpretable Reinforcement Learning
In Posters Wed
Abhinav Verma · Vijayaraghavan Murali · Rishabh Singh · Pushmeet Kohli · Swarat Chaudhuri
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #34
Structured Evolution with Compact Architectures for Scalable Policy Optimization
In Posters Wed
Krzysztof Choromanski · Mark Rowland · Vikas Sindhwani · Richard E Turner · Adrian Weller
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #35
The Weighted Kendall and High-order Kernels for Permutations
In Posters Wed
Yunlong Jiao · Jean-Philippe Vert
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #36
The Limits of Maxing, Ranking, and Preference Learning
In Posters Wed
Moein Falahatgar · Ayush Jain · Alon Orlitsky · Venkatadheeraj Pichapati · Vaishakh Ravindrakumar
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #37
Black Box FDR
In Posters Wed
Wesley Tansey · Yixin Wang · David Blei · Raul Rabadan
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #38
Variable Selection via Penalized Neural Network: a Drop-Out-One Loss Approach
In Posters Wed
Mao Ye · Yan Sun
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #39
Clustering Semi-Random Mixtures of Gaussians
In Posters Wed
Aravindan Vijayaraghavan · Pranjal Awasthi
[ PDF]  [ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #40
Leveraging Well-Conditioned Bases: Streaming and Distributed Summaries in Minkowski $p$-Norms
In Posters Wed
Charlie Dickens · Graham Cormode · David Woodruff
[ PDF]  [ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #41
Learning by Playing - Solving Sparse Reward Tasks from Scratch
In Posters Wed
Martin Riedmiller · Roland Hafner · Thomas Lampe · Michael Neunert · Jonas Degrave · Tom Van de Wiele · Vlad Mnih · Nicolas Heess · Jost Springenberg
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #42
Structured Control Nets for Deep Reinforcement Learning
In Posters Wed
Mario Srouji · Jian Zhang · Ruslan Salakhutdinov
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #43
Stagewise Safe Bayesian Optimization with Gaussian Processes
In Posters Wed
Yanan Sui · Vincent Zhuang · Joel Burdick · Yisong Yue
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #44
Bayesian Optimization of Combinatorial Structures
In Posters Wed
Ricardo Baptista · Matthias Poloczek
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #45
GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models
In Posters Wed
Jiaxuan You · Rex (Zhitao) Ying · Xiang Ren · Will Hamilton · Jure Leskovec
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #46
Dependent Relational Gamma Process Models for Longitudinal Networks
In Posters Wed
Sikun Yang · Heinz Koeppl
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #47
K-means clustering using random matrix sparsification
In Posters Wed
Kaushik Sinha
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #48
Hierarchical Clustering with Structural Constraints
In Posters Wed
Evangelos Chatziafratis · Rad Niazadeh · Moses Charikar
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #49
Kronecker Recurrent Units
In Posters Wed
Cijo Jose · Mouhamadou Moustapha Cisse · Francois Fleuret
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #50
Semi-Supervised Learning via Compact Latent Space Clustering
In Posters Wed
Konstantinos Kamnitsas · Daniel C. Castro · Loic Le Folgoc · Ian Walker · Ryutaro Tanno · Daniel Rueckert · Ben Glocker · Antonio Criminisi · Aditya Nori
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #51
Dynamic Evaluation of Neural Sequence Models
In Posters Wed
Ben Krause · Emmanuel Kahembwe · Iain Murray · Steve Renals
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #52
TACO: Learning Task Decomposition via Temporal Alignment for Control
In Posters Wed
Kyriacos Shiarlis · Markus Wulfmeier · Sasha Salter · Shimon Whiteson · Ingmar Posner
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #53
A Spectral Approach to Gradient Estimation for Implicit Distributions
In Posters Wed
Jiaxin Shi · Shengyang Sun · Jun Zhu
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #54
Quasi-Monte Carlo Variational Inference
In Posters Wed
Alexander Buchholz · Florian Wenzel · Stephan Mandt
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #55
Learning to Optimize Combinatorial Functions
In Posters Wed
Nir Rosenfeld · Eric Balkanski · Amir Globerson · Yaron Singer
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #56
Proportional Allocation: Simple, Distributed, and Diverse Matching with High Entropy
In Posters Wed
Shipra Agarwal · Morteza Zadimoghaddam · Vahab Mirrokni
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #57
Representation Learning on Graphs with Jumping Knowledge Networks
In Posters Wed
Keyulu Xu · Chengtao Li · Yonglong Tian · Tomohiro Sonobe · Ken-ichi Kawarabayashi · Stefanie Jegelka
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #58
NetGAN: Generating Graphs via Random Walks
In Posters Wed
Aleksandar Bojchevski · Oleksandr Shchur · Daniel Zügner · Stephan Günnemann
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #59
INSPECTRE: Privately Estimating the Unseen
In Posters Wed
Jayadev Acharya · Gautam Kamath · Ziteng Sun · Huanyu Zhang
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #60
Locally Private Hypothesis Testing
In Posters Wed
Or Sheffet
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #61
Latent Space Policies for Hierarchical Reinforcement Learning
In Posters Wed
Tuomas Haarnoja · Kristian Hartikainen · Pieter Abbeel · Sergey Levine
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #62
More Robust Doubly Robust Off-policy Evaluation
In Posters Wed
Mehrdad Farajtabar · Yinlam Chow · Mohammad Ghavamzadeh
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #63
Learning to Explain: An Information-Theoretic Perspective on Model Interpretation
In Posters Wed
Jianbo Chen · Le Song · Martin Wainwright · Michael Jordan
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #64
End-to-end Active Object Tracking via Reinforcement Learning
In Posters Wed
Wenhan Luo · Peng Sun · Fangwei Zhong · Wei Liu · Tong Zhang · Yizhou Wang
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #65
Efficient and Consistent Adversarial Bipartite Matching
In Posters Wed
Rizal Fathony · Sima Behpour · Xinhua Zhang · Brian Ziebart
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #66
SparseMAP: Differentiable Sparse Structured Inference
In Posters Wed
Vlad Niculae · Andre Filipe Torres Martins · Mathieu Blondel · Claire Cardie
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #67
Bilevel Programming for Hyperparameter Optimization and Meta-Learning
In Posters Wed
Luca Franceschi · Paolo Frasconi · Saverio Salzo · Riccardo Grazzi · Massimiliano Pontil
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #68
Meta-Learning by Adjusting Priors Based on Extended PAC-Bayes Theory
In Posters Wed
Ron Amit · Ron Meir
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #69
Parameterized Algorithms for the Matrix Completion Problem
In Posters Wed
Robert Ganian · DePaul Iyad Kanj · Sebastian Ordyniak · Stefan Szeider
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #70
Nearly Optimal Robust Subspace Tracking
In Posters Wed
Praneeth Narayanamurthy · Namrata Vaswani
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #71
Katyusha X: Simple Momentum Method for Stochastic Sum-of-Nonconvex Optimization
In Posters Wed
Zeyuan Allen-Zhu
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #72
signSGD: Compressed Optimisation for Non-Convex Problems
In Posters Wed
Jeremy Bernstein · Yu-Xiang Wang · Kamyar Azizzadenesheli · Anima Anandkumar
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #73
Synthesizing Robust Adversarial Examples
In Posters Wed
Anish Athalye · Logan Engstrom · Andrew Ilyas · Kevin Kwok
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #74
Differentiable Abstract Interpretation for Provably Robust Neural Networks
In Posters Wed
Matthew Mirman · Timon Gehr · Martin Vechev
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #75
Stochastic Training of Graph Convolutional Networks with Variance Reduction
In Posters Wed
Jianfei Chen · Jun Zhu · Le Song
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #76
Neural Relational Inference for Interacting Systems
In Posters Wed
Thomas Kipf · Ethan Fetaya · Kuan-Chieh Wang · Max Welling · Richard Zemel
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #77
Which Training Methods for GANs do actually Converge?
In Posters Wed
Lars Mescheder · Andreas Geiger · Sebastian Nowozin
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #78
Learning Independent Causal Mechanisms
In Posters Wed
Giambattista Parascandolo · Niki Kilbertus · Mateo Rojas-Carulla · Bernhard Schölkopf
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #79
Nonconvex Optimization for Regression with Fairness Constraints
In Posters Wed
Junpei Komiyama · Akiko Takeda · Junya Honda · Hajime Shimao
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #80
Fairness Without Demographics in Repeated Loss Minimization
In Posters Wed
Tatsunori Hashimoto · Megha Srivastava · Hongseok Namkoong · Percy Liang
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #81
MSplit LBI: Realizing Feature Selection and Dense Estimation Simultaneously in Few-shot and Zero-shot Learning
In Posters Wed
Bo Zhao · Xinwei Sun · Yanwei Fu · Yuan Yao · Yizhou Wang
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #82
Nonoverlap-Promoting Variable Selection
In Posters Wed
Pengtao Xie · Hongbao Zhang · Yichen Zhu · Eric Xing
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #83
Towards More Efficient Stochastic Decentralized Learning: Faster Convergence and Sparse Communication
In Posters Wed
Zebang Shen · Aryan Mokhtari · Tengfei Zhou · Peilin Zhao · Hui Qian
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #84
Graph Networks as Learnable Physics Engines for Inference and Control
In Posters Wed
Alvaro Sanchez-Gonzalez · Nicolas Heess · Jost Springenberg · Josh Merel · Martin Riedmiller · Raia Hadsell · Peter Battaglia
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #85
An Alternative View: When Does SGD Escape Local Minima?
In Posters Wed
Bobby Kleinberg · Yuanzhi Li · Yang Yuan
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #86
Asynchronous Decentralized Parallel Stochastic Gradient Descent
In Posters Wed
Xiangru Lian · Wei Zhang · Ce Zhang · Ji Liu
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #87
An Estimation and Analysis Framework for the Rasch Model
In Posters Wed
Andrew Lan · Mung Chiang · Christoph Studer
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #88
Mitigating Bias in Adaptive Data Gathering via Differential Privacy
In Posters Wed
Seth Neel · Aaron Roth
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #89
Local Private Hypothesis Testing: Chi-Square Tests
In Posters Wed
Marco Gaboardi · Ryan Rogers
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #90
Disentangling by Factorising
In Posters Wed
Hyunjik Kim · Andriy Mnih
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #91
Efficient Bias-Span-Constrained Exploration-Exploitation in Reinforcement Learning
In Posters Wed
Ronan Fruit · Matteo Pirotta · Alessandro Lazaric · Ronald Ortner
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #92
Learning to search with MCTSnets
In Posters Wed
Arthur Guez · Theophane Weber · Ioannis Antonoglou · Karen Simonyan · Oriol Vinyals · Daan Wierstra · Remi Munos · David Silver
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #93
Decoupled Parallel Backpropagation with Convergence Guarantee
In Posters Wed
Zhouyuan Huo · Bin Gu · Qian Yang · Heng Huang
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #94
On Learning Sparsely Used Dictionaries from Incomplete Samples
In Posters Wed
Thanh Nguyen · Akshay Soni · Chinmay Hegde
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #95
Variational Network Inference: Strong and Stable with Concrete Support
In Posters Wed
Amir Dezfouli · Edwin Bonilla · Richard Nock
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #96
Weakly Submodular Maximization Beyond Cardinality Constraints: Does Randomization Help Greedy?
In Posters Wed
Lin Chen · Moran Feldman · Amin Karbasi
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #97
Data Summarization at Scale: A Two-Stage Submodular Approach
In Posters Wed
Marko Mitrovic · Ehsan Kazemi · Morteza Zadimoghaddam · Amin Karbasi
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #98
Best Arm Identification in Linear Bandits with Linear Dimension Dependency
In Posters Wed
Chao Tao · Saúl A. Blanco · Yuan Zhou
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #99
Learning with Abandonment
In Posters Wed
Sven Schmit · Ramesh Johari
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #100
Hyperbolic Entailment Cones for Learning Hierarchical Embeddings
In Posters Wed
Octavian-Eugen Ganea · Gary Becigneul · Thomas Hofmann
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #101
Generative Temporal Models with Spatial Memory for Partially Observed Environments
In Posters Wed
Marco Fraccaro · Danilo J. Rezende · Yori Zwols · Alexander Pritzel · S. M. Ali Eslami · Fabio Viola
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #102
DiCE: The Infinitely Differentiable Monte Carlo Estimator
In Posters Wed
Jakob Foerster · Gregory Farquhar · Maruan Al-Shedivat · Tim Rocktäschel · Eric Xing · Shimon Whiteson
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #103
Orthogonal Recurrent Neural Networks with Scaled Cayley Transform
In Posters Wed
Kyle Helfrich · Devin Willmott · Qiang Ye
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #104
Least-Squares Temporal Difference Learning for the Linear Quadratic Regulator
In Posters Wed
Stephen Tu · Benjamin Recht
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #105
Spotlight: Optimizing Device Placement for Training Deep Neural Networks
In Posters Wed
Yuanxiang Gao · Li Chen · Baochun Li
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #106
Universal Planning Networks: Learning Generalizable Representations for Visuomotor Control
In Posters Wed
Aravind Srinivas · Allan Jabri · Pieter Abbeel · Sergey Levine · Chelsea Finn
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #107
Coordinated Exploration in Concurrent Reinforcement Learning
In Posters Wed
Maria Dimakopoulou · Benjamin Van Roy
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #108
A probabilistic framework for multi-view feature learning with many-to-many associations via neural networks
In Posters Wed
Akifumi Okuno · Tetsuya Hada · Hidetoshi Shimodaira
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #109
Learning Steady-States of Iterative Algorithms over Graphs
In Posters Wed
Hanjun Dai · Zornitsa Kozareva · Bo Dai · Alex Smola · Le Song
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #110
Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples
In Posters Wed
Anish Athalye · Nicholas Carlini · David Wagner
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #111
Fair and Diverse DPP-Based Data Summarization
In Posters Wed
L. Elisa Celis · Vijay Keswani · Damian Straszak · Amit Jayant Deshpande · Tarun Kathuria · Nisheeth Vishnoi
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #112
Learning Implicit Generative Models with the Method of Learned Moments
In Posters Wed
Suman Ravuri · Shakir Mohamed · Mihaela Rosca · Oriol Vinyals
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #113
Chi-square Generative Adversarial Network
In Posters Wed
Chenyang Tao · Liqun Chen · Ricardo Henao · Jianfeng Feng · Lawrence Carin
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #114
Streaming Principal Component Analysis in Noisy Setting
In Posters Wed
Teodor Vanislavov Marinov · Poorya Mianjy · Raman Arora
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #115
Partial Optimality and Fast Lower Bounds for Weighted Correlation Clustering
In Posters Wed
Jan-Hendrik Lange · Andreas Karrenbauer · Bjoern Andres
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #116
SGD and Hogwild! Convergence Without the Bounded Gradients Assumption
In Posters Wed
Lam Nguyen · PHUONG_HA NGUYEN · Marten van Dijk · Peter Richtarik · Katya Scheinberg · Martin Takac
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #117
Computational Optimal Transport: Complexity by Accelerated Gradient Descent Is Better Than by Sinkhorn's Algorithm
In Posters Wed
Pavel Dvurechenskii · Alexander Gasnikov · Alexey Kroshnin
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #118
Stability and Generalization of Learning Algorithms that Converge to Global Optima
In Posters Wed
Zachary Charles · Dimitris Papailiopoulos
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #119
Optimal Rates of Sketched-regularized Algorithms for Least-Squares Regression over Hilbert Spaces
In Posters Wed
Junhong Lin · Volkan Cevher
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #120
Adafactor: Adaptive Learning Rates with Sublinear Memory Cost
In Posters Wed
Noam Shazeer · Mitchell Stern
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #121
Fast Parametric Learning with Activation Memorization
In Posters Wed
Jack Rae · Chris Dyer · Peter Dayan · Timothy Lillicrap
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #122
Essentially No Barriers in Neural Network Energy Landscape
In Posters Wed
Felix Draxler · Kambis Veschgini · Manfred Salmhofer · Fred Hamprecht
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #123
Deep Linear Networks with Arbitrary Loss: All Local Minima Are Global
In Posters Wed
Thomas Laurent · James von Brecht
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #124
Generalized Robust Bayesian Committee Machine for Large-scale Gaussian Process Regression
In Posters Wed
Haitao Liu · Jianfei Cai · Yi Wang · Yew Soon ONG
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #125
Bayesian Quadrature for Multiple Related Integrals
In Posters Wed
Xiaoyue Xi · Francois-Xavier Briol · Mark Girolami
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #126
Deep Predictive Coding Network for Object Recognition
In Posters Wed
Haiguang Wen · Kuan Han · Junxing Shi · Yizhen Zhang · Eugenio Culurciello · Zhongming Liu
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #127
Neural Inverse Rendering for General Reflectance Photometric Stereo
In Posters Wed
Tatsunori Taniai · Takanori Maehara
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #128
On the Relationship between Data Efficiency and Error for Uncertainty Sampling
In Posters Wed
Stephen Mussmann · Percy Liang
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #129
Selecting Representative Examples for Program Synthesis
In Posters Wed
Yewen Pu · Zachery Miranda · Armando Solar-Lezama · Leslie Kaelbling
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #130
Conditional Neural Processes
In Posters Wed
Marta Garnelo · Dan Rosenbaum · Chris Maddison · Tiago Ramalho · David Saxton · Murray Shanahan · Yee Teh · Danilo J. Rezende · S. M. Ali Eslami
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #131
Hierarchical Long-term Video Prediction without Supervision
In Posters Wed
Nevan Wichers · Ruben Villegas · Dumitru Erhan · Honglak Lee
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #132
Adversarial Risk and the Dangers of Evaluating Against Weak Attacks
In Posters Wed
Jonathan Uesato · Brendan O'Donoghue · Pushmeet Kohli · Aäron van den Oord
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #133
A Classification-Based Study of Covariate Shift in GAN Distributions
In Posters Wed
Shibani Santurkar · Ludwig Schmidt · Aleksander Madry
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #134
Gated Path Planning Networks
In Posters Wed
Lisa Lee · Emilio Parisotto · Devendra Singh Chaplot · Eric Xing · Ruslan Salakhutdinov
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #135
Automatic Goal Generation for Reinforcement Learning Agents
In Posters Wed
Carlos Florensa · David Held · Xinyang Geng · Pieter Abbeel
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #136
ADMM and Accelerated ADMM as Continuous Dynamical Systems
In Posters Wed
Guilherme Franca · Daniel Robinson · Rene Vidal
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #137
Dissipativity Theory for Accelerating Stochastic Variance Reduction: A Unified Analysis of SVRG and Katyusha Using Semidefinite Programs
In Posters Wed
Bin Hu · Stephen Wright · Laurent Lessard
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #138
Contextual Graph Markov Model: A Deep and Generative Approach to Graph Processing
In Posters Wed
Davide Bacciu · Federico Errica · Alessio Micheli
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #139
Learning Continuous Hierarchies in the Lorentz Model of Hyperbolic Geometry
In Posters Wed
Maximilian Nickel · Douwe Kiela
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #140
Fast Variance Reduction Method with Stochastic Batch Size
In Posters Wed
University of California Xuanqing Liu · Cho-Jui Hsieh
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #141
Lyapunov Functions for First-Order Methods: Tight Automated Convergence Guarantees
In Posters Wed
Adrien Taylor · Bryan Van Scoy · Laurent Lessard
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #142
Nonparametric Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information
In Posters Wed
Yichong Xu · Hariank Muthakana · Sivaraman Balakrishnan · Aarti Singh · Artur Dubrawski
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #143
The Well-Tempered Lasso
In Posters Wed
Yuanzhi Li · Yoram Singer
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #144
Transfer Learning via Learning to Transfer
In Posters Wed
Ying WEI · Yu Zhang · Junzhou Huang · Qiang Yang
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #145
Pseudo-task Augmentation: From Deep Multitask Learning to Intratask Sharing—and Back
In Posters Wed
Elliot Meyerson · Risto Miikkulainen
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #146
Analysis of Minimax Error Rate for Crowdsourcing and Its Application to Worker Clustering Model
In Posters Wed
Hideaki Imamura · Issei Sato · Masashi Sugiyama
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #147
Deep One-Class Classification
In Posters Wed
Lukas Ruff · Nico Görnitz · Lucas Deecke · Shoaib Ahmed Siddiqui · Robert Vandermeulen · Alexander Binder · Emmanuel Müller · Marius Kloft
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #148
Binary Partitions with Approximate Minimum Impurity
In Posters Wed
Eduardo Laber · Marco Molinaro · Felipe de A. Mello Pereira
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #149
Beyond 1/2-Approximation for Submodular Maximization on Massive Data Streams
In Posters Wed
Ashkan Norouzi-Fard · Jakub Tarnawski · Slobodan Mitrovic · Amir Zandieh · Aidasadat Mousavifar · Ola Svensson
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #150
Yes, but Did It Work?: Evaluating Variational Inference
In Posters Wed
Yuling Yao · Aki Vehtari · Daniel Simpson · Andrew Gelman
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #151
Black-Box Variational Inference for Stochastic Differential Equations
In Posters Wed
Tom Ryder · Andrew Golightly · Stephen McGough · Dennis Prangle
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #152
Online Convolutional Sparse Coding with Sample-Dependent Dictionary
In Posters Wed
Yaqing WANG · Quanming Yao · James Kwok · Lionel NI
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #153
Learning to Speed Up Structured Output Prediction
In Posters Wed
Xingyuan Pan · Vivek Srikumar
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #154
Differentially Private Identity and Equivalence Testing of Discrete Distributions
In Posters Wed
Maryam Aliakbarpour · Ilias Diakonikolas · MIT Ronitt Rubinfeld
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #155
Information Theoretic Guarantees for Empirical Risk Minimization with Applications to Model Selection and Large-Scale Optimization
In Posters Wed
Ibrahim Alabdulmohsin
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #156
BOCK : Bayesian Optimization with Cylindrical Kernels
In Posters Wed
ChangYong Oh · Efstratios Gavves · Max Welling
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #157
BOHB: Robust and Efficient Hyperparameter Optimization at Scale
In Posters Wed
Stefan Falkner · Aaron Klein · Frank Hutter
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #158
Distributed Nonparametric Regression under Communication Constraints
In Posters Wed
Yuancheng Zhu · John Lafferty
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #159
Optimal Tuning for Divide-and-conquer Kernel Ridge Regression with Massive Data
In Posters Wed
Ganggang Xu · Zuofeng Shang · Guang Cheng
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #160
WHInter: A Working set algorithm for High-dimensional sparse second order Interaction models
In Posters Wed
Marine LE MORVAN · Jean-Philippe Vert
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #161
Safe Element Screening for Submodular Function Minimization
In Posters Wed
Weizhong Zhang · Bin Hong · Lin Ma · Wei Liu · Tong Zhang
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #162
Feedback-Based Tree Search for Reinforcement Learning
In Posters Wed
Daniel Jiang · Emmanuel Ekwedike · Han Liu
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #163
Transfer in Deep Reinforcement Learning Using Successor Features and Generalised Policy Improvement
In Posters Wed
Andre Barreto · Diana Borsa · John Quan · Tom Schaul · David Silver · Matteo Hessel · Daniel J. Mankowitz · Augustin Zidek · Remi Munos
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #164
Data-Dependent Stability of Stochastic Gradient Descent
In Posters Wed
Ilja Kuzborskij · Christoph H. Lampert
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #165
LeapsAndBounds: A Method for Approximately Optimal Algorithm Configuration
In Posters Wed
Gellért Weisz · András György · Csaba Szepesvari
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #166
Scalable Deletion-Robust Submodular Maximization: Data Summarization with Privacy and Fairness Constraints
In Posters Wed
Ehsan Kazemi · Morteza Zadimoghaddam · Amin Karbasi
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #167
Covariate Adjusted Precision Matrix Estimation via Nonconvex Optimization
In Posters Wed
Jinghui Chen · Pan Xu · Lingxiao Wang · Jian Ma · Quanquan Gu
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #168
Comparing Dynamics: Deep Neural Networks versus Glassy Systems
In Posters Wed
Marco Baity-Jesi · Levent Sagun · Mario Geiger · Stefano Spigler · Gerard Arous · Chiara Cammarota · Yann LeCun · Matthieu Wyart · Giulio Biroli
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #169
An Optimal Control Approach to Deep Learning and Applications to Discrete-Weight Neural Networks
In Posters Wed
Qianxiao Li · IHPC Shuji Hao
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #170
Not All Samples Are Created Equal: Deep Learning with Importance Sampling
In Posters Wed
Angelos Katharopoulos · Francois Fleuret
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #171
Dynamical Isometry and a Mean Field Theory of CNNs: How to Train 10,000-Layer Vanilla Convolutional Neural Networks
In Posters Wed
Lechao Xiao · Yasaman Bahri · Jascha Sohl-Dickstein · Samuel Schoenholz · Jeffrey Pennington
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #172
Path Consistency Learning in Tsallis Entropy Regularized MDPs
In Posters Wed
Yinlam Chow · Ofir Nachum · Mohammad Ghavamzadeh
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #173
Lipschitz Continuity in Model-based Reinforcement Learning
In Posters Wed
Kavosh Asadi · Dipendra Misra · Michael L. Littman
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #174___0
Bounds on the Approximation Power of Feedforward Neural Networks
In Posters Wed
Mohammad Mehrabi · Aslan Tchamkerten · MANSOOR I YOUSEFI
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #174___1
Linear Spectral Estimators and an Application to Phase Retrieval
In Posters Wed
Ramina Ghods · Andrew Lan · Tom Goldstein · Christoph Studer
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #175
Testing Sparsity over Known and Unknown Bases
In Posters Wed
Siddharth Barman · Arnab Bhattacharyya · Suprovat Ghoshal
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #176
Inference Suboptimality in Variational Autoencoders
In Posters Wed
Chris Cremer · Xuechen Li · David Duvenaud
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #177
Semi-Implicit Variational Inference
In Posters Wed
Mingzhang Yin · Mingyuan Zhou
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #178
Variance Regularized Counterfactual Risk Minimization via Variational Divergence Minimization
In Posters Wed
Hang Wu · May Wang
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #179
Limits of Estimating Heterogeneous Treatment Effects: Guidelines for Practical Algorithm Design
In Posters Wed
Ahmed M. Alaa · Mihaela van der Schaar
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #180
A Semantic Loss Function for Deep Learning with Symbolic Knowledge
In Posters Wed
Jingyi Xu · Zilu Zhang · Tal Friedman · Yitao Liang · Guy Van den Broeck
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #181
Stabilizing Gradients for Deep Neural Networks via Efficient SVD Parameterization
In Posters Wed
Jiong Zhang · Qi Lei · Inderjit Dhillon
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #182
An Efficient Semismooth Newton based Algorithm for Convex Clustering
In Posters Wed
Yancheng Yuan · Defeng Sun · Kim-Chuan Toh
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #183
Lightweight Stochastic Optimization for Minimizing Finite Sums with Infinite Data
In Posters Wed
Shuai Zheng · James Kwok
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #184
Exploiting the Potential of Standard Convolutional Autoencoders for Image Restoration by Evolutionary Search
In Posters Wed
Masanori SUGANUMA · Mete Ozay · Takayuki Okatani
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #185
Efficient Neural Architecture Search via Parameters Sharing
In Posters Wed
Hieu Pham · Melody Guan · Barret Zoph · Quoc Le · Jeff Dean
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #186
Non-convex Conditional Gradient Sliding
In Posters Wed
chao qu · Yan Li · Huan Xu
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #187
Stochastic Variance-Reduced Cubic Regularized Newton Method
In Posters Wed
Dongruo Zhou · Pan Xu · Quanquan Gu
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #188
On the Optimization of Deep Networks: Implicit Acceleration by Overparameterization
In Posters Wed
Sanjeev Arora · Nadav Cohen · Elad Hazan
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #189
The Dynamics of Learning: A Random Matrix Approach
In Posters Wed
Zhenyu Liao · Romain Couillet
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #190
Learning K-way D-dimensional Discrete Codes for Compact Embedding Representations
In Posters Wed
Ting Chen · Martin Min · Yizhou Sun
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #191
Discovering Interpretable Representations for Both Deep Generative and Discriminative Models
In Posters Wed
Tameem Adel · Zoubin Ghahramani · Adrian Weller
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #192
Continuous-Time Flows for Efficient Inference and Density Estimation
In Posters Wed
Changyou Chen · Chunyuan Li · Liquan Chen · Wenlin Wang · Yunchen Pu · Lawrence Carin
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #193
Tighter Variational Bounds are Not Necessarily Better
In Posters Wed
Tom Rainforth · Adam Kosiorek · Tuan Anh Le · Chris Maddison · Maximilian Igl · Frank Wood · Yee-Whye Teh
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #194
PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learning
In Posters Wed
Yunbo Wang · Zhifeng Gao · Mingsheng Long · Jianmin Wang · Philip Yu
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #195
RadialGAN: Leveraging multiple datasets to improve target-specific predictive models using Generative Adversarial Networks
In Posters Wed
Jinsung Yoon · James Jordon · Mihaela van der Schaar
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #196
Differentiable Compositional Kernel Learning for Gaussian Processes
In Posters Wed
Shengyang Sun · Guodong Zhang · Chaoqi Wang · Wenyuan Zeng · Jiaman Li · Roger Grosse
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #197
Markov Modulated Gaussian Cox Processes for Semi-Stationary Intensity Modeling of Events Data
In Posters Wed
Minyoung Kim
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #198
Improved Regret Bounds for Thompson Sampling in Linear Quadratic Control Problems
In Posters Wed
Marc Abeille · Alessandro Lazaric
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #199
Design of Experiments for Model Discrimination Hybridising Analytical and Data-Driven Approaches
In Posters Wed
Simon Olofsson · Marc P Deisenroth · Ruth Misener
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #200
Anonymous Walk Embeddings
In Posters Wed
Sergey Ivanov · Evgeny Burnaev
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #201
Improving Optimization in Models With Continuous Symmetry Breaking
In Posters Wed
Robert Bamler · Stephan Mandt
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #202
Conditional Noise-Contrastive Estimation of Unnormalised Models
In Posters Wed
Ciwan Ceylan · Michael Gutmann
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #203
Canonical Tensor Decomposition for Knowledge Base Completion
In Posters Wed
Timothee Lacroix · Nicolas Usunier · Guillaume Obozinski
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #204
The Power of Interpolation: Understanding the Effectiveness of SGD in Modern Over-parametrized Learning
In Posters Wed
Siyuan Ma · Raef Bassily · Mikhail Belkin
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #205
A Simple Stochastic Variance Reduced Algorithm with Fast Convergence Rates
In Posters Wed
Kaiwen Zhou · Fanhua Shang · James Cheng
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #206
Escaping Saddles with Stochastic Gradients
In Posters Wed
Hadi Daneshmand · Jonas Kohler · Aurelien Lucchi · Thomas Hofmann
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #207
$D^2$: Decentralized Training over Decentralized Data
In Posters Wed
Hanlin Tang · Xiangru Lian · Ming Yan · Ce Zhang · Ji Liu
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #208
Machine Theory of Mind
In Posters Wed
Neil Rabinowitz · Frank Perbet · Francis Song · Chiyuan Zhang · S. M. Ali Eslami · Matthew Botvinick
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #209
Been There, Done That: Meta-Learning with Episodic Recall
In Posters Wed
Samuel Ritter · Jane Wang · Zeb Kurth-Nelson · Siddhant Jayakumar · Charles Blundell · Razvan Pascanu · Matthew Botvinick
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #210
Faster Derivative-Free Stochastic Algorithm for Shared Memory Machines
In Posters Wed
Bin Gu · Zhouyuan Huo · Cheng Deng · Heng Huang
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #211
Coded Sparse Matrix Multiplication
In Posters Wed
Sinong Wang · Jiashang Liu · Ness Shroff
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #212
Augment and Reduce: Stochastic Inference for Large Categorical Distributions
In Posters Wed
Francisco Ruiz · Michalis Titsias · Adji Bousso Dieng · David Blei
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #213
Efficient Gradient-Free Variational Inference using Policy Search
In Posters Wed
Oleg Arenz · Gerhard Neumann · Mingjun Zhong
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #214
Fixing a Broken ELBO
In Posters Wed
Alexander Alemi · Ben Poole · Ian Fischer · Joshua V Dillon · Rif Saurous · Kevin Murphy
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #215
Variational Inference and Model Selection with Generalized Evidence Bounds
In Posters Wed
Liqun Chen · Chenyang Tao · RUIYI (ROY) ZHANG · Ricardo Henao · Lawrence Carin
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #216
The Generalization Error of Dictionary Learning with Moreau Envelopes
In Posters Wed
ALEXANDROS GEORGOGIANNIS
[ PDF] 
Poster
Wed Jul 11 09:15 AM -- 12:00 PM (PDT) @ Hall B #217
Network Global Testing by Counting Graphlets
In Posters Wed
Jiashun Jin · Zheng Ke · Shengming Luo
[ PDF] 
Break
Wed Jul 11 10:30 AM -- 11:00 AM (PDT) @ Hall B
Coffee Break
Break
Wed Jul 11 12:00 PM -- 01:30 PM (PDT)
Lunch - on your own
Break
Wed Jul 11 03:30 PM -- 04:00 PM (PDT) @ Hall B
Coffee Break
Break
Wed Jul 11 06:15 PM -- 07:15 PM (PDT) @ Hall B
Light Evening Snack