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Invited Talk
Thu Jul 12 12:00 AM -- 01:00 AM (PDT) @ A1
Intelligence per Kilowatthour
Max Welling
[ Slides]  [ Video] 
Session
Thu Jul 12 01:00 AM -- 01:20 AM (PDT) @ A1
Best Paper Session 2
Oral
Thu Jul 12 02:00 AM -- 02:20 AM (PDT) @ A4
Learning unknown ODE models with Gaussian processes
In Gaussian Processes 2
Markus Heinonen · Cagatay Yildiz · Henrik Mannerström · Jukka Intosalmi · Harri Lähdesmäki
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:00 AM -- 02:20 AM (PDT) @ K11
Probabilistic Boolean Tensor Decomposition
In Matrix Factorization 1
Tammo Rukat · Christopher Holmes · Christopher Yau
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:00 AM -- 02:20 AM (PDT) @ A3
Learning Policy Representations in Multiagent Systems
In Multi-Agent Learning 1
Aditya Grover · Maruan Al-Shedivat · Jayesh K. Gupta · Yura Burda · Harrison Edwards
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:00 AM -- 02:20 AM (PDT) @ A6
Multicalibration: Calibration for the (Computationally-Identifiable) Masses
In Privacy, Anonymity, and Security 2
Ursula Hebert-Johnson · Michael Kim · Omer Reingold · Guy Rothblum
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:00 AM -- 02:20 AM (PDT) @ A1
Convergent Tree Backup and Retrace with Function Approximation
In Reinforcement Learning 8
Ahmed Touati · Pierre-Luc Bacon · Doina Precup · Pascal Vincent
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:00 AM -- 02:20 AM (PDT) @ A5
Learning Maximum-A-Posteriori Perturbation Models for Structured Prediction in Polynomial Time
In Structured Prediction 2
Asish Ghoshal · Jean Honorio
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:00 AM -- 02:20 AM (PDT) @ Victoria
Not to Cry Wolf: Distantly Supervised Multitask Learning in Critical Care
In Deep Learning (Neural Network Architectures) 6
Patrick Schwab · Emanuela Keller · Carl Muroi · David J. Mack · Christian Strässle · Walter Karlen
[ PDF] 
Oral
Thu Jul 12 02:00 AM -- 02:20 AM (PDT) @ A7
Geometry Score: A Method For Comparing Generative Adversarial Networks
In Generative Models 2
Valentin Khrulkov · Ivan Oseledets
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:00 AM -- 02:20 AM (PDT) @ K1
Learning Memory Access Patterns
In Other Applications 2
Milad Hashemi · Kevin Swersky · Jamie Smith · Grant Ayers · Heiner Litz · Jichuan Chang · Christos Kozyrakis · Parthasarathy Ranganathan
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:00 AM -- 02:20 AM (PDT) @ A9
Exploring Hidden Dimensions in Accelerating Convolutional Neural Networks
In Parallel and Distributed Learning 2
Zhihao Jia · Sina Lin · Charles Qi · Alex Aiken
[ PDF] 
Oral
Thu Jul 12 02:20 AM -- 02:40 AM (PDT) @ A9
Error Compensated Quantized SGD and its Applications to Large-scale Distributed Optimization
In Parallel and Distributed Learning 2
Jiaxiang Wu · Weidong Huang · Junzhou Huang · Tong Zhang
[ PDF] 
Oral
Thu Jul 12 02:20 AM -- 02:40 AM (PDT) @ Victoria
Compressing Neural Networks using the Variational Information Bottelneck
In Deep Learning (Neural Network Architectures) 6
Bin Dai · Chen Zhu · Baining Guo · David Wipf
[ PDF] 
Oral
Thu Jul 12 02:20 AM -- 02:30 AM (PDT) @ K11
A Primal-Dual Analysis of Global Optimality in Nonconvex Low-Rank Matrix Recovery
In Matrix Factorization 1
Xiao Zhang · Lingxiao Wang · Yaodong Yu · Quanquan Gu
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:20 AM -- 02:40 AM (PDT) @ K1
Geodesic Convolutional Shape Optimization
In Other Applications 2
Pierre Baque · Edoardo Remelli · Francois Fleuret · EPFL Pascal Fua
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:20 AM -- 02:40 AM (PDT) @ A1
SBEED: Convergent Reinforcement Learning with Nonlinear Function Approximation
In Reinforcement Learning 8
Bo Dai · Albert Shaw · Lihong Li · Lin Xiao · Niao He · Zhen Liu · Jianshu Chen · Le Song
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:20 AM -- 02:30 AM (PDT) @ A3
Learning to Coordinate with Coordination Graphs in Repeated Single-Stage Multi-Agent Decision Problems
In Multi-Agent Learning 1
Eugenio Bargiacchi · Timothy Verstraeten · Diederik Roijers · Ann Nowé · Hado van Hasselt
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:20 AM -- 02:30 AM (PDT) @ A7
Optimizing the Latent Space of Generative Networks
In Generative Models 2
Piotr Bojanowski · Armand Joulin · David Lopez-Paz · Arthur Szlam
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:20 AM -- 02:40 AM (PDT) @ A5
Differentiable Dynamic Programming for Structured Prediction and Attention
In Structured Prediction 2
Arthur Mensch · Mathieu Blondel
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:20 AM -- 02:30 AM (PDT) @ A6
Residual Unfairness in Fair Machine Learning from Prejudiced Data
In Privacy, Anonymity, and Security 2
Nathan Kallus · Angela Zhou
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:20 AM -- 02:40 AM (PDT) @ A4
Constraining the Dynamics of Deep Probabilistic Models
In Gaussian Processes 2
Marco Lorenzi · Maurizio Filippone
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:30 AM -- 02:40 AM (PDT) @ K11
Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval and Matrix Completion
In Matrix Factorization 1
Cong Ma · Kaizheng Wang · Yuejie Chi · Yuxin Chen
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:30 AM -- 02:40 AM (PDT) @ A3
Learning to Act in Decentralized Partially Observable MDPs
In Multi-Agent Learning 1
Jilles Dibangoye · Olivier Buffet
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:30 AM -- 02:40 AM (PDT) @ A6
Improving the Gaussian Mechanism for Differential Privacy: Analytical Calibration and Optimal Denoising
In Privacy, Anonymity, and Security 2
Borja de Balle Pigem · Yu-Xiang Wang
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:30 AM -- 02:40 AM (PDT) @ A7
Adversarial Learning with Local Coordinate Coding
In Generative Models 2
Jiezhang Cao · Yong Guo · Qingyao Wu · Chunhua Shen · Junzhou Huang · Mingkui Tan
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:40 AM -- 02:50 AM (PDT) @ A7
Learning Representations and Generative Models for 3D Point Clouds
In Generative Models 2
Panagiotis Achlioptas · Olga Diamanti · Ioannis Mitliagkas · Leonidas Guibas
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:40 AM -- 02:50 AM (PDT) @ K11
Learning Binary Latent Variable Models: A Tensor Eigenpair Approach
In Matrix Factorization 1
Ariel Jaffe · Roi Weiss · Boaz Nadler · Shai Carmi · Yuval Kluger
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:40 AM -- 02:50 AM (PDT) @ A9
DICOD: Distributed Convolutional Coordinate Descent for Convolutional Sparse Coding
In Parallel and Distributed Learning 2
Thomas Moreau · Laurent Oudre · Nicolas Vayatis
[ PDF] 
Oral
Thu Jul 12 02:40 AM -- 02:50 AM (PDT) @ A6
Improving the Privacy and Accuracy of ADMM-Based Distributed Algorithms
In Privacy, Anonymity, and Security 2
Xueru Zhang · Mohammad Mahdi Khalili · Mingyan Liu
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:40 AM -- 02:50 AM (PDT) @ Victoria
Kernelized Synaptic Weight Matrices
In Deep Learning (Neural Network Architectures) 6
Lorenz Müller · Julien Martel · Giacomo Indiveri
[ PDF] 
Oral
Thu Jul 12 02:40 AM -- 02:50 AM (PDT) @ A1
Scalable Bilinear Pi Learning Using State and Action Features
In Reinforcement Learning 8
Yichen Chen · Lihong Li · Mengdi Wang
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:40 AM -- 02:50 AM (PDT) @ A4
Probabilistic Recurrent State-Space Models
In Gaussian Processes 2
Andreas Doerr · Christian Daniel · Martin Schiegg · Duy Nguyen-Tuong · Stefan Schaal · Marc Toussaint · Sebastian Trimpe
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:40 AM -- 02:50 AM (PDT) @ A3
Modeling Others using Oneself in Multi-Agent Reinforcement Learning
In Multi-Agent Learning 1
Roberta Raileanu · Emily Denton · Arthur Szlam · Facebook Rob Fergus
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:40 AM -- 02:50 AM (PDT) @ A5
Structured Output Learning with Abstention: Application to Accurate Opinion Prediction
In Structured Prediction 2
Alexandre Garcia · Telecom-ParisTech Chloé Clavel · Slim Essid · Florence d'Alche-Buc
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:40 AM -- 02:50 AM (PDT) @ K1
AutoPrognosis: Automated Clinical Prognostic Modeling via Bayesian Optimization with Structured Kernel Learning
In Other Applications 2
Ahmed M. Alaa · Mihaela van der Schaar
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:50 AM -- 03:00 AM (PDT) @ A7
Theoretical Analysis of Image-to-Image Translation with Adversarial Learning
In Generative Models 2
Xudong Pan · Mi Zhang · Daizong Ding
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:50 AM -- 03:00 AM (PDT) @ A1
Stochastic Variance-Reduced Policy Gradient
In Reinforcement Learning 8
Matteo Papini · Damiano Binaghi · Giuseppe Canonaco · Matteo Pirotta · Marcello Restelli
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:50 AM -- 03:00 AM (PDT) @ A9
Distributed Asynchronous Optimization with Unbounded Delays: How Slow Can You Go?
In Parallel and Distributed Learning 2
Zhengyuan Zhou · Panayotis Mertikopoulos · Nicholas Bambos · Peter Glynn · Yinyu Ye · Li-Jia Li · Li Fei-Fei
[ PDF] 
Oral
Thu Jul 12 02:50 AM -- 03:00 AM (PDT) @ A3
QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning
In Multi-Agent Learning 1
Tabish Rashid · Mikayel Samvelyan · Christian Schroeder · Gregory Farquhar · Jakob Foerster · Shimon Whiteson
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:50 AM -- 03:00 AM (PDT) @ A6
Adversarial Regression with Multiple Learners
In Privacy, Anonymity, and Security 2
Liang Tong · Sixie Yu · Scott Alfeld · Yevgeniy Vorobeychik
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:50 AM -- 03:00 AM (PDT) @ K11
Closed-form Marginal Likelihood in Gamma-Poisson Matrix Factorization
In Matrix Factorization 1
Louis Filstroff · Alberto Lumbreras · Cedric Fevotte
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:50 AM -- 03:00 AM (PDT) @ Victoria
Deep Models of Interactions Across Sets
In Deep Learning (Neural Network Architectures) 6
Jason Hartford · Devon Graham · Kevin Leyton-Brown · Siamak Ravanbakhsh
[ PDF] 
Oral
Thu Jul 12 02:50 AM -- 03:00 AM (PDT) @ K1
TAPAS: Tricks to Accelerate (encrypted) Prediction As a Service
In Other Applications 2
Amartya Sanyal · Matt Kusner · Adria Gascon · Varun Kanade
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:50 AM -- 03:00 AM (PDT) @ A5
End-to-End Learning for the Deep Multivariate Probit Model
In Structured Prediction 2
Di Chen · Yexiang Xue · Carla Gomes
[ PDF]  [ Video] 
Oral
Thu Jul 12 02:50 AM -- 03:00 AM (PDT) @ A4
Structured Variationally Auto-encoded Optimization
In Gaussian Processes 2
Xiaoyu Lu · Javier González · Zhenwen Dai · Neil Lawrence
[ PDF]  [ Video] 
Oral
Thu Jul 12 04:30 AM -- 04:50 AM (PDT) @ A4
Error Estimation for Randomized Least-Squares Algorithms via the Bootstrap
In Monte Carlo Methods 1
Miles Lopes · Shusen Wang · Michael Mahoney
[ PDF]  [ Video] 
Oral
Thu Jul 12 04:30 AM -- 04:50 AM (PDT) @ Victoria
Focused Hierarchical RNNs for Conditional Sequence Processing
In Deep Learning (Neural Network Architectures) 7
Rosemary Nan Ke · Konrad Zolna · Alessandro Sordoni · Zhouhan Lin · Adam Trischler · Yoshua Bengio · Joelle Pineau · Laurent Charlin · Christopher Pal
[ PDF] 
Oral
Thu Jul 12 04:30 AM -- 04:50 AM (PDT) @ A9
Shampoo: Preconditioned Stochastic Tensor Optimization
In Optimization (Convex) 3
Vineet Gupta · Tomer Koren · Yoram Singer
[ PDF] 
Oral
Thu Jul 12 04:30 AM -- 04:50 AM (PDT) @ K11
Improved large-scale graph learning through ridge spectral sparsification
In Large Scale Learning and Big Data 1
Daniele Calandriello · Alessandro Lazaric · Ioannis Koutis · Michal Valko
[ PDF]  [ Video] 
Oral
Thu Jul 12 04:30 AM -- 04:50 AM (PDT) @ K1
Learning One Convolutional Layer with Overlapping Patches
In Deep Learning (Theory) 3
Surbhi Goel · Adam Klivans · Raghu Meka
[ PDF]  [ Video] 
Oral
Thu Jul 12 04:30 AM -- 04:50 AM (PDT) @ A5
Accelerated Spectral Ranking
In Ranking and Preference Learning 2
Arpit Agarwal · Prathamesh Patil · Shivani Agarwal
[ PDF]  [ Video] 
Oral
Thu Jul 12 04:30 AM -- 04:50 AM (PDT) @ A7
Composite Functional Gradient Learning of Generative Adversarial Models
In Deep Learning (Adversarial) 2
Rie Johnson · Tong Zhang
[ PDF]  [ Video] 
Oral
Thu Jul 12 04:30 AM -- 04:50 AM (PDT) @ A6
Inductive Two-Layer Modeling with Parametric Bregman Transfer
In Supervised Learning 1
Vignesh Ganapathiraman · Zhan Shi · Xinhua Zhang · Yaoliang Yu
[ PDF]  [ Video] 
Oral
Thu Jul 12 04:30 AM -- 04:50 AM (PDT) @ A3
Fast Information-theoretic Bayesian Optimisation
In Optimization (Bayesian) 2
Binxin Ru · Michael A Osborne · Mark Mcleod · Diego Granziol
[ PDF]  [ Video] 
Oral
Thu Jul 12 04:30 AM -- 04:50 AM (PDT) @ A1
Investigating Human Priors for Playing Video Games
In Reinforcement Learning 9
Rachit Dubey · Pulkit Agrawal · Deepak Pathak · Tom Griffiths · Alexei Efros
[ PDF]  [ Video] 
Oral
Thu Jul 12 04:50 AM -- 05:00 AM (PDT) @ A5
Composite Marginal Likelihood Methods for Random Utility Models
In Ranking and Preference Learning 2
Zhibing Zhao · Lirong Xia
[ PDF]  [ Video] 
Oral
Thu Jul 12 04:50 AM -- 05:00 AM (PDT) @ A6
Does Distributionally Robust Supervised Learning Give Robust Classifiers?
In Supervised Learning 1
Weihua Hu · Gang Niu · Issei Sato · Masashi Sugiyama
[ PDF]  [ Video] 
Oral
Thu Jul 12 04:50 AM -- 05:10 AM (PDT) @ K11
Parallel and Streaming Algorithms for K-Core Decomposition
In Large Scale Learning and Big Data 1
Hossein Esfandiari · Silvio Lattanzi · Vahab Mirrokni
[ PDF]  [ Video] 
Oral
Thu Jul 12 04:50 AM -- 05:00 AM (PDT) @ A1
Can Deep Reinforcement Learning Solve Erdos-Selfridge-Spencer Games?
In Reinforcement Learning 9
Maithra Raghu · Alexander Irpan · Jacob Andreas · Bobby Kleinberg · Quoc Le · Jon Kleinberg
[ PDF]  [ Video] 
Oral
Thu Jul 12 04:50 AM -- 05:10 AM (PDT) @ A3
Optimization, fast and slow: optimally switching between local and Bayesian optimization
In Optimization (Bayesian) 2
Mark McLeod · Stephen Roberts · Michael A Osborne
[ PDF]  [ Video] 
Oral
Thu Jul 12 04:50 AM -- 05:00 AM (PDT) @ A9
Characterizing Implicit Bias in Terms of Optimization Geometry
In Optimization (Convex) 3
Suriya Gunasekar · Jason Lee · Daniel Soudry · Nati Srebro
[ PDF] 
Oral
Thu Jul 12 04:50 AM -- 05:10 AM (PDT) @ K1
Gradient Descent Learns One-hidden-layer CNN: Don't be Afraid of Spurious Local Minima
In Deep Learning (Theory) 3
Simon Du · Jason Lee · Yuandong Tian · Aarti Singh · Barnabás Póczos
[ PDF]  [ Video] 
Oral
Thu Jul 12 04:50 AM -- 05:10 AM (PDT) @ Victoria
Learn from Your Neighbor: Learning Multi-modal Mappings from Sparse Annotations
In Deep Learning (Neural Network Architectures) 7
Ashwin Kalyan · Stefan Lee · Anitha Kannan · Dhruv Batra
[ PDF] 
Oral
Thu Jul 12 04:50 AM -- 05:00 AM (PDT) @ A7
Tempered Adversarial Networks
In Deep Learning (Adversarial) 2
Mehdi S. M. Sajjadi · Giambattista Parascandolo · Arash Mehrjou · Bernhard Schölkopf
[ PDF]  [ Video] 
Oral
Thu Jul 12 04:50 AM -- 05:00 AM (PDT) @ A4
Asynchronous Stochastic Quasi-Newton MCMC for Non-Convex Optimization
In Monte Carlo Methods 1
Umut Simsekli · Cagatay Yildiz · Thanh Huy Nguyen · Ali Taylan Cemgil · Gaël RICHARD
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:00 AM -- 05:10 AM (PDT) @ A4
Stochastic Variance-Reduced Hamilton Monte Carlo Methods
In Monte Carlo Methods 1
Difan Zou · Pan Xu · Quanquan Gu
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:00 AM -- 05:10 AM (PDT) @ A7
Improved Training of Generative Adversarial Networks Using Representative Features
In Deep Learning (Adversarial) 2
Duhyeon Bang · Hyunjung Shim
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:00 AM -- 05:10 AM (PDT) @ A1
GEP-PG: Decoupling Exploration and Exploitation in Deep Reinforcement Learning Algorithms
In Reinforcement Learning 9
Cédric Colas · Olivier Sigaud · Pierre-Yves Oudeyer
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:00 AM -- 05:10 AM (PDT) @ A9
A Distributed Second-Order Algorithm You Can Trust
In Optimization (Convex) 3
Celestine Mendler-Dünner · Aurelien Lucchi · Matilde Gargiani · Yatao Bian · Thomas Hofmann · Martin Jaggi
[ PDF] 
Oral
Thu Jul 12 05:00 AM -- 05:10 AM (PDT) @ A6
Prediction Rule Reshaping
In Supervised Learning 1
Matt Bonakdarpour · Sabyasachi Chatterjee · Rina Barber · John Lafferty
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:00 AM -- 05:10 AM (PDT) @ A5
Ranking Distributions based on Noisy Sorting
In Ranking and Preference Learning 2
Adil El Mesaoudi-Paul · Eyke Hüllermeier · Robert Busa-Fekete
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:10 AM -- 05:20 AM (PDT) @ A1
Time Limits in Reinforcement Learning
In Reinforcement Learning 9
Fabio Pardo · Arash Tavakoli · Vitaly Levdik · Petar Kormushev
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:10 AM -- 05:20 AM (PDT) @ Victoria
Learning long term dependencies via Fourier recurrent units
In Deep Learning (Neural Network Architectures) 7
Jiong Zhang · Yibo Lin · Zhao Song · Inderjit Dhillon
[ PDF] 
Oral
Thu Jul 12 05:10 AM -- 05:20 AM (PDT) @ A3
Batch Bayesian Optimization via Multi-objective Acquisition Ensemble for Automated Analog Circuit Design
In Optimization (Bayesian) 2
Wenlong Lyu · Fan Yang · Changhao Yan · Dian Zhou · Xuan Zeng
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:10 AM -- 05:20 AM (PDT) @ K1
The Multilinear Structure of ReLU Networks
In Deep Learning (Theory) 3
Thomas Laurent · James von Brecht
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:10 AM -- 05:20 AM (PDT) @ A9
A Delay-tolerant Proximal-Gradient Algorithm for Distributed Learning
In Optimization (Convex) 3
Konstantin Mishchenko · Franck Iutzeler · Jérôme Malick · Massih-Reza Amini
[ PDF] 
Oral
Thu Jul 12 05:10 AM -- 05:20 AM (PDT) @ A7
A Two-Step Computation of the Exact GAN Wasserstein Distance
In Deep Learning (Adversarial) 2
Huidong Liu · Xianfeng GU · Samaras Dimitris
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:10 AM -- 05:20 AM (PDT) @ A6
Finding Influential Training Samples for Gradient Boosted Decision Trees
In Supervised Learning 1
Boris Sharchilev · Yury Ustinovskiy · Pavel Serdyukov · Maarten de Rijke
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:10 AM -- 05:20 AM (PDT) @ K11
Fast Approximate Spectral Clustering for Dynamic Networks
In Large Scale Learning and Big Data 1
Lionel Martin · Andreas Loukas · Pierre Vandergheynst
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:10 AM -- 05:20 AM (PDT) @ A4
A Robust Approach to Sequential Information Theoretic Planning
In Monte Carlo Methods 1
Sue Zheng · Jason Pacheco · John Fisher
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:10 AM -- 05:20 AM (PDT) @ A5
SQL-Rank: A Listwise Approach to Collaborative Ranking
In Ranking and Preference Learning 2
LIWEI WU · Cho-Jui Hsieh · University of California James Sharpnack
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:20 AM -- 05:30 AM (PDT) @ A3
Tight Regret Bounds for Bayesian Optimization in One Dimension
In Optimization (Bayesian) 2
Jonathan Scarlett
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:20 AM -- 05:30 AM (PDT) @ A6
Noise2Noise: Learning Image Restoration without Clean Data
In Supervised Learning 1
Jaakko Lehtinen · Jacob Munkberg · Jon Hasselgren · Samuli Laine · Tero Karras · Miika Aittala · Timo Aila
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:20 AM -- 05:30 AM (PDT) @ A1
Visualizing and Understanding Atari Agents
In Reinforcement Learning 9
Samuel Greydanus · Anurag Koul · Jonathan Dodge · Alan Fern
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:20 AM -- 05:30 AM (PDT) @ A9
Gradient Coding from Cyclic MDS Codes and Expander Graphs
In Optimization (Convex) 3
Netanel Raviv · Rashish Tandon · Alexandros Dimakis · Itzhak Tamo
[ PDF] 
Oral
Thu Jul 12 05:20 AM -- 05:30 AM (PDT) @ A4
Discrete-Continuous Mixtures in Probabilistic Programming: Generalized Semantics and Inference Algorithms
In Monte Carlo Methods 1
Yi Wu · Siddharth Srivastava · Nicholas Hay · Simon Du · Stuart Russell
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:20 AM -- 05:30 AM (PDT) @ K1
Understanding the Loss Surface of Neural Networks for Binary Classification
In Deep Learning (Theory) 3
SHIYU LIANG · Ruoyu Sun · Yixuan Li · R Srikant
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:20 AM -- 05:30 AM (PDT) @ K11
Matrix Norms in Data Streams: Faster, Multi-Pass and Row-Order
In Large Scale Learning and Big Data 1
Vladimir Braverman · Stephen Chestnut · Robert Krauthgamer · Yi Li · David Woodruff · Lin Yang
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:20 AM -- 05:30 AM (PDT) @ Victoria
Training Neural Machines with Trace-Based Supervision
In Deep Learning (Neural Network Architectures) 7
Matthew Mirman · Dimitar Dimitrov · Pavle Djordjevic · Timon Gehr · Martin Vechev
[ PDF] 
Oral
Thu Jul 12 05:20 AM -- 05:30 AM (PDT) @ A7
Is Generator Conditioning Causally Related to GAN Performance?
In Deep Learning (Adversarial) 2
Augustus Odena · Jacob Buckman · Catherine Olsson · Tom B Brown · Christopher Olah · Colin Raffel · Ian Goodfellow
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:20 AM -- 05:30 AM (PDT) @ A5
Extreme Learning to Rank via Low Rank Assumption
In Ranking and Preference Learning 2
Minhao Cheng · Ian Davidson · Cho-Jui Hsieh
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:30 AM -- 05:50 AM (PDT) @ A7
Black-box Adversarial Attacks with Limited Queries and Information
In Deep Learning (Adversarial) 3
Andrew Ilyas · Logan Engstrom · Anish Athalye · Jessy Lin
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:30 AM -- 05:50 AM (PDT) @ A9
Alternating Randomized Block Coordinate Descent
In Optimization (Convex) 4
Jelena Diakonikolas · Orecchia Lorenzo
[ PDF] 
Oral
Thu Jul 12 05:30 AM -- 05:50 AM (PDT) @ A6
Dimensionality-Driven Learning with Noisy Labels
In Supervised Learning 2
Xingjun Ma · Yisen Wang · Michael E. Houle · Shuo Zhou · Sarah Erfani · Shutao Xia · Sudanthi Wijewickrema · James Bailey
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:30 AM -- 05:50 AM (PDT) @ A3
To Understand Deep Learning We Need to Understand Kernel Learning
In Kernel Methods 1
Mikhail Belkin · Siyuan Ma · Soumik Mandal
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:30 AM -- 05:50 AM (PDT) @ K1
Tropical Geometry of Deep Neural Networks
In Deep Learning (Theory) 4
Liwen Zhang · Gregory Naisat · Lek-Heng Lim
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:30 AM -- 05:50 AM (PDT) @ Victoria
Neural Dynamic Programming for Musical Self Similarity
In Deep Learning (Neural Network Architectures) 8
Christian Walder · Dongwoo Kim
[ PDF] 
Oral
Thu Jul 12 05:30 AM -- 05:50 AM (PDT) @ A5
Feasible Arm Identification
In Online Learning 1
Julian Katz-Samuels · Clay Scott
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:30 AM -- 05:50 AM (PDT) @ K11
Near Optimal Frequent Directions for Sketching Dense and Sparse Matrices
In Large Scale Learning and Big Data 2
Zengfeng Huang
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:30 AM -- 05:50 AM (PDT) @ A1
The Mirage of Action-Dependent Baselines in Reinforcement Learning
In Reinforcement Learning 10
George Tucker · Surya Bhupatiraju · Shixiang Gu · Richard E Turner · Zoubin Ghahramani · Sergey Levine
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:30 AM -- 05:50 AM (PDT) @ A4
Robust and Scalable Models of Microbiome Dynamics
In Graphical Models 1
Travis Gibson · Georg Gerber
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:50 AM -- 06:10 AM (PDT) @ K1
A Spline Theory of Deep Learning
In Deep Learning (Theory) 4
Randall Balestriero · Richard Baraniuk
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:50 AM -- 06:10 AM (PDT) @ A3
Kernel Recursive ABC: Point Estimation with Intractable Likelihood
In Kernel Methods 1
Takafumi Kajihara · Motonobu Kanagawa · Keisuke Yamazaki · Kenji Fukumizu
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:50 AM -- 06:10 AM (PDT) @ A1
Smoothed Action Value Functions for Learning Gaussian Policies
In Reinforcement Learning 10
Ofir Nachum · Mohammad Norouzi · George Tucker · Dale Schuurmans
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:50 AM -- 06:00 AM (PDT) @ A6
MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted Labels
In Supervised Learning 2
Lu Jiang · Zhengyuan Zhou · Thomas Leung · Li-Jia Li · Li Fei-Fei
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:50 AM -- 06:00 AM (PDT) @ K11
Loss Decomposition for Fast Learning in Large Output Spaces
In Large Scale Learning and Big Data 2
En-Hsu Yen · Satyen Kale · Felix Xinnan Yu · Daniel Holtmann-Rice · Sanjiv Kumar · Pradeep Ravikumar
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:50 AM -- 06:00 AM (PDT) @ A4
Stein Variational Message Passing for Continuous Graphical Models
In Graphical Models 1
Dilin Wang · Zhe Zeng · Qiang Liu
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:50 AM -- 06:10 AM (PDT) @ A5
Bandits with Delayed, Aggregated Anonymous Feedback
In Online Learning 1
Ciara Pike-Burke · Shipra Agrawal · Csaba Szepesvari · Steffen Grünewälder
[ PDF]  [ Video] 
Oral
Thu Jul 12 05:50 AM -- 06:10 AM (PDT) @ A7
Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples
In Deep Learning (Adversarial) 3
Anish Athalye · Nicholas Carlini · David Wagner
[ PDF] 
Oral
Thu Jul 12 05:50 AM -- 06:10 AM (PDT) @ A9
Randomized Block Cubic Newton Method
In Optimization (Convex) 4
Nikita Doikov · Peter Richtarik
[ PDF] 
Oral
Thu Jul 12 05:50 AM -- 06:00 AM (PDT) @ Victoria
A Hierarchical Latent Vector Model for Learning Long-Term Structure in Music
In Deep Learning (Neural Network Architectures) 8
Adam Roberts · Jesse Engel · Colin Raffel · Curtis Hawthorne · Douglas Eck
[ PDF] 
Oral
Thu Jul 12 06:00 AM -- 06:10 AM (PDT) @ Victoria
Fast Decoding in Sequence Models Using Discrete Latent Variables
In Deep Learning (Neural Network Architectures) 8
Lukasz Kaiser · Samy Bengio · Aurko Roy · Ashish Vaswani · Niki Parmar · Jakob Uszkoreit · Noam Shazeer
[ PDF] 
Oral
Thu Jul 12 06:00 AM -- 06:10 AM (PDT) @ A6
Learning to Reweight Examples for Robust Deep Learning
In Supervised Learning 2
Mengye Ren · Wenyuan Zeng · Bin Yang · Raquel Urtasun
[ PDF]  [ Video] 
Oral
Thu Jul 12 06:00 AM -- 06:10 AM (PDT) @ K11
Ultra Large-Scale Feature Selection using Count-Sketches
In Large Scale Learning and Big Data 2
Amirali Aghazadeh · Ryan Spring · Daniel LeJeune · Gautam Dasarathy · Anshumali Shrivastava · Richard Baraniuk
[ PDF]  [ Video] 
Oral
Thu Jul 12 06:00 AM -- 06:10 AM (PDT) @ A4
A Fast and Scalable Joint Estimator for Integrating Additional Knowledge in Learning Multiple Related Sparse Gaussian Graphical Models
In Graphical Models 1
Beilun Wang · Arshdeep Sekhon · Yanjun Qi
[ PDF]  [ Video] 
Oral
Thu Jul 12 06:10 AM -- 06:20 AM (PDT) @ A1
Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor
In Reinforcement Learning 10
Tuomas Haarnoja · Aurick Zhou · Pieter Abbeel · Sergey Levine
[ PDF] 
Oral
Thu Jul 12 06:10 AM -- 06:20 AM (PDT) @ K1
Neural Networks Should Be Wide Enough to Learn Disconnected Decision Regions
In Deep Learning (Theory) 4
Quynh Nguyen · Mahesh Mukkamala · Matthias Hein
[ PDF]  [ Video] 
Oral
Thu Jul 12 06:10 AM -- 06:20 AM (PDT) @ K11
Approximate Leave-One-Out for Fast Parameter Tuning in High Dimensions
In Large Scale Learning and Big Data 2
Shuaiwen Wang · Wenda Zhou · Haihao Lu · Arian Maleki · Vahab Mirrokni
[ PDF]  [ Video] 
Oral
Thu Jul 12 06:10 AM -- 06:20 AM (PDT) @ A6
Curriculum Learning by Transfer Learning: Theory and Experiments with Deep Networks
In Supervised Learning 2
Daphna Weinshall · Gad A Cohen · Dan Amir
[ PDF]  [ Video] 
Oral
Thu Jul 12 06:10 AM -- 06:20 AM (PDT) @ A3
Differentially Private Database Release via Kernel Mean Embeddings
In Kernel Methods 1
Matej Balog · Ilya Tolstikhin · Bernhard Schölkopf
[ PDF]  [ Video] 
Oral
Thu Jul 12 06:10 AM -- 06:20 AM (PDT) @ A5
Make the Minority Great Again: First-Order Regret Bound for Contextual Bandits
In Online Learning 1
Zeyuan Allen-Zhu · Sebastien Bubeck · Yuanzhi Li
[ PDF]  [ Video] 
Oral
Thu Jul 12 06:10 AM -- 06:20 AM (PDT) @ Victoria
PixelSNAIL: An Improved Autoregressive Generative Model
In Deep Learning (Neural Network Architectures) 8
Xi Chen · Nikhil Mishra · Mostafa Rohaninejad · Pieter Abbeel
[ PDF] 
Oral
Thu Jul 12 06:10 AM -- 06:20 AM (PDT) @ A4
Large-Scale Sparse Inverse Covariance Estimation via Thresholding and Max-Det Matrix Completion
In Graphical Models 1
Richard Zhang · Salar Fattahi · Somayeh Sojoudi
[ PDF]  [ Video] 
Oral
Thu Jul 12 06:10 AM -- 06:20 AM (PDT) @ A7
Adversarial Attack on Graph Structured Data
In Deep Learning (Adversarial) 3
Hanjun Dai · Hui Li · Tian Tian · Xin Huang · Lin Wang · Jun Zhu · Le Song
[ PDF] 
Oral
Thu Jul 12 06:10 AM -- 06:20 AM (PDT) @ A9
Accelerating Greedy Coordinate Descent Methods
In Optimization (Convex) 4
Haihao Lu · Robert Freund · Vahab Mirrokni
[ PDF] 
Oral
Thu Jul 12 06:20 AM -- 06:30 AM (PDT) @ A9
On Acceleration with Noise-Corrupted Gradients
In Optimization (Convex) 4
Michael Cohen · Jelena Diakonikolas · Orecchia Lorenzo
[ PDF] 
Oral
Thu Jul 12 06:20 AM -- 06:30 AM (PDT) @ A3
Learning in Reproducing Kernel Kreı̆n Spaces
In Kernel Methods 1
Dino Oglic · Thomas Gaertner
[ PDF]  [ Video] 
Oral
Thu Jul 12 06:20 AM -- 06:30 AM (PDT) @ A5
Thompson Sampling for Combinatorial Semi-Bandits
In Online Learning 1
Siwei Wang · Wei Chen
[ PDF]  [ Video] 
Oral
Thu Jul 12 06:20 AM -- 06:30 AM (PDT) @ A1
Addressing Function Approximation Error in Actor-Critic Methods
In Reinforcement Learning 10
Scott Fujimoto · Herke van Hoof · David Meger
[ PDF]  [ Video] 
Oral
Thu Jul 12 06:20 AM -- 06:30 AM (PDT) @ K1
Stronger Generalization Bounds for Deep Nets via a Compression Approach
In Deep Learning (Theory) 4
Sanjeev Arora · Rong Ge · Behnam Neyshabur · Yi Zhang
[ PDF]  [ Video] 
Oral
Thu Jul 12 06:20 AM -- 06:30 AM (PDT) @ Victoria
Image Transformer
In Deep Learning (Neural Network Architectures) 8
Niki Parmar · Ashish Vaswani · Jakob Uszkoreit · Lukasz Kaiser · Noam Shazeer · Alexander Ku · Dustin Tran
[ PDF] 
Oral
Thu Jul 12 06:20 AM -- 06:30 AM (PDT) @ A6
Improving Regression Performance with Distributional Losses
In Supervised Learning 2
Ehsan Imani · Martha White
[ PDF]  [ Video] 
Oral
Thu Jul 12 06:20 AM -- 06:30 AM (PDT) @ A4
Bucket Renormalization for Approximate Inference
In Graphical Models 1
Sungsoo Ahn · Michael Chertkov · Adrian Weller · Jinwoo Shin
[ PDF]  [ Video] 
Oral
Thu Jul 12 06:20 AM -- 06:30 AM (PDT) @ A7
GAIN: Missing Data Imputation using Generative Adversarial Nets
In Deep Learning (Adversarial) 3
Jinsung Yoon · James Jordon · Mihaela van der Schaar
[ PDF] 
Oral
Thu Jul 12 06:20 AM -- 06:30 AM (PDT) @ K11
Semi-Supervised Learning on Data Streams via Temporal Label Propagation
In Large Scale Learning and Big Data 2
Tal Wagner · Sudipto Guha · Shiva Kasiviswanathan · Nina Mishra
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:00 AM -- 07:20 AM (PDT) @ A5
Projection-Free Online Optimization with Stochastic Gradient: From Convexity to Submodularity
In Online Learning 2
Lin Chen · Christopher Harshaw · Hamed Hassani · Amin Karbasi
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:00 AM -- 07:20 AM (PDT) @ Victoria
Using Inherent Structures to design Lean 2-layer RBMs
In Deep Learning (Neural Network Architectures) 9
Abhishek Bansal · Abhinav Anand · Chiranjib Bhattacharyya
[ PDF] 
Oral
Thu Jul 12 07:00 AM -- 07:20 AM (PDT) @ A3
Towards End-to-End Prosody Transfer for Expressive Speech Synthesis with Tacotron
In Natural Language and Speech Processing 1
RJ Skerry-Ryan · Eric Battenberg · Ying Xiao · Yuxuan Wang · Daisy Stanton · Joel Shor · Ron Weiss · Robert Clark · Rif Saurous
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:00 AM -- 07:20 AM (PDT) @ A6
Optimal Distributed Learning with Multi-pass Stochastic Gradient Methods
In Statistical Learning Theory 4
Junhong Lin · Volkan Cevher
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:00 AM -- 07:20 AM (PDT) @ A7
The Mechanics of n-Player Differentiable Games
In Deep Learning (Adversarial) 4
David Balduzzi · Sebastien Racaniere · James Martens · Jakob Foerster · Karl Tuyls · Thore Graepel
[ PDF] 
Oral
Thu Jul 12 07:00 AM -- 07:20 AM (PDT) @ A1
Configurable Markov Decision Processes
In Reinforcement Learning 11
Alberto Maria Metelli · Mirco Mutti · Marcello Restelli
[ PDF] 
Oral
Thu Jul 12 07:00 AM -- 07:20 AM (PDT) @ K11
Decentralized Submodular Maximization: Bridging Discrete and Continuous Settings
In Optimization (Combinatorial) 3
Aryan Mokhtari · Hamed Hassani · Amin Karbasi
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:00 AM -- 07:20 AM (PDT) @ K1
Reviving and Improving Recurrent Back-Propagation
In Deep Learning (Theory) 5
Renjie Liao · Yuwen Xiong · Ethan Fetaya · Lisa Zhang · KiJung Yoon · Zachary S Pitkow · Raquel Urtasun · Richard Zemel
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:00 AM -- 07:20 AM (PDT) @ A9
Approximate message passing for amplitude based optimization
In Optimization (Non-convex) 3
Junjie Ma · Ji Xu · Arian Maleki
[ PDF] 
Oral
Thu Jul 12 07:00 AM -- 07:20 AM (PDT) @ A4
Variational Bayesian dropout: pitfalls and fixes
In Deep Learning (Bayesian) 2
Jiri Hron · Alexander Matthews · Zoubin Ghahramani
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:20 AM -- 07:30 AM (PDT) @ Victoria
Deep Asymmetric Multi-task Feature Learning
In Deep Learning (Neural Network Architectures) 9
Hae Beom Lee · Eunho Yang · Sung Ju Hwang
[ PDF] 
Oral
Thu Jul 12 07:20 AM -- 07:30 AM (PDT) @ K1
Dynamical Isometry and a Mean Field Theory of RNNs: Gating Enables Signal Propagation in Recurrent Neural Networks
In Deep Learning (Theory) 5
Minmin Chen · Jeffrey Pennington · Samuel Schoenholz
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:20 AM -- 07:40 AM (PDT) @ A9
Dissecting Adam: The Sign, Magnitude and Variance of Stochastic Gradients
In Optimization (Non-convex) 3
Lukas Balles · Philipp Hennig
[ PDF] 
Oral
Thu Jul 12 07:20 AM -- 07:30 AM (PDT) @ A4
Accurate Uncertainties for Deep Learning Using Calibrated Regression
In Deep Learning (Bayesian) 2
Volodymyr Kuleshov · Nathan Fenner · Stefano Ermon
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:20 AM -- 07:30 AM (PDT) @ K11
Approximation Guarantees for Adaptive Sampling
In Optimization (Combinatorial) 3
Eric Balkanski · Yaron Singer
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:20 AM -- 07:40 AM (PDT) @ A1
Beyond the One-Step Greedy Approach in Reinforcement Learning
In Reinforcement Learning 11
Yonathan Efroni · Gal Dalal · Bruno Scherrer · Shie Mannor
[ PDF] 
Oral
Thu Jul 12 07:20 AM -- 07:30 AM (PDT) @ A7
K-Beam Minimax: Efficient Optimization for Deep Adversarial Learning
In Deep Learning (Adversarial) 4
Jihun Hamm · Yung-Kyun Noh
[ PDF] 
Oral
Thu Jul 12 07:20 AM -- 07:40 AM (PDT) @ A5
Practical Contextual Bandits with Regression Oracles
In Online Learning 2
Dylan Foster · Alekh Agarwal · Miroslav Dudik · Haipeng Luo · Robert Schapire
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:20 AM -- 07:40 AM (PDT) @ A6
Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates
In Statistical Learning Theory 4
Dong Yin · Yudong Chen · Kannan Ramchandran · Peter Bartlett
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:20 AM -- 07:40 AM (PDT) @ A3
Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis
In Natural Language and Speech Processing 1
Yuxuan Wang · Daisy Stanton · Yu Zhang · RJ-Skerry Ryan · Eric Battenberg · Joel Shor · Ying Xiao · Ye Jia · Fei Ren · Rif Saurous
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:30 AM -- 07:40 AM (PDT) @ K1
Invariance of Weight Distributions in Rectified MLPs
In Deep Learning (Theory) 5
Susumu Tsuchida · Fred Roosta · Marcus Gallagher
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:30 AM -- 07:40 AM (PDT) @ A4
Decomposition of Uncertainty in Bayesian Deep Learning for Efficient and Risk-sensitive Learning
In Deep Learning (Bayesian) 2
Stefan Depeweg · Jose Miguel Hernandez-Lobato · Finale Doshi-Velez · Steffen Udluft
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:30 AM -- 07:40 AM (PDT) @ Victoria
Beyond Finite Layer Neural Networks: Bridging Deep Architectures and Numerical Differential Equations
In Deep Learning (Neural Network Architectures) 9
Yiping Lu · Aoxiao Zhong · Quanzheng Li · Bin Dong
[ PDF] 
Oral
Thu Jul 12 07:30 AM -- 07:40 AM (PDT) @ A7
First Order Generative Adversarial Networks
In Deep Learning (Adversarial) 4
Calvin Seward · Thomas Unterthiner · Urs M Bergmann · Nikolay Jetchev · Sepp Hochreiter
[ PDF] 
Oral
Thu Jul 12 07:30 AM -- 07:40 AM (PDT) @ K11
Greed is Still Good: Maximizing Monotone Submodular+Supermodular (BP) Functions
In Optimization (Combinatorial) 3
Wenruo Bai · Jeff Bilmes
[ PDF] 
Oral
Thu Jul 12 07:40 AM -- 07:50 AM (PDT) @ Victoria
Extracting Automata from Recurrent Neural Networks Using Queries and Counterexamples
In Deep Learning (Neural Network Architectures) 9
Gail Weiss · Yoav Goldberg · Eran Yahav
[ PDF] 
Oral
Thu Jul 12 07:40 AM -- 07:50 AM (PDT) @ K11
Constrained Interacting Submodular Groupings
In Optimization (Combinatorial) 3
Andrew Cotter · Mahdi Milani Fard · Seungil You · Maya Gupta · Jeff Bilmes
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:40 AM -- 07:50 AM (PDT) @ A5
Fast Stochastic AUC Maximization with $O(1/n)$-Convergence Rate
In Online Learning 2
Mingrui Liu · Xiaoxuan Zhang · Zaiyi Chen · Xiaoyu Wang · Tianbao Yang
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:40 AM -- 07:50 AM (PDT) @ A4
Scalable approximate Bayesian inference for particle tracking data
In Deep Learning (Bayesian) 2
Ruoxi Sun · Department of Statistics Liam Paninski
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:40 AM -- 07:50 AM (PDT) @ A9
prDeep: Robust Phase Retrieval with a Flexible Deep Network
In Optimization (Non-convex) 3
Christopher Metzler · Phillip Schniter · Ashok Veeraraghavan · Richard Baraniuk
[ PDF] 
Oral
Thu Jul 12 07:40 AM -- 07:50 AM (PDT) @ A3
Fitting New Speakers Based on a Short Untranscribed Sample
In Natural Language and Speech Processing 1
Eliya Nachmani · Adam Polyak · Yaniv Taigman · Lior Wolf
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:40 AM -- 07:50 AM (PDT) @ A1
Policy and Value Transfer in Lifelong Reinforcement Learning
In Reinforcement Learning 11
David Abel · Yuu Jinnai · Sophie Guo · George Konidaris · Michael L. Littman
[ PDF] 
Oral
Thu Jul 12 07:40 AM -- 07:50 AM (PDT) @ K1
Learning Dynamics of Linear Denoising Autoencoders
In Deep Learning (Theory) 5
Arnu Pretorius · Steve Kroon · Herman Kamper
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:40 AM -- 07:50 AM (PDT) @ A6
Functional Gradient Boosting based on Residual Network Perception
In Statistical Learning Theory 4
Atsushi Nitanda · Taiji Suzuki
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:40 AM -- 07:50 AM (PDT) @ A7
Towards Fast Computation of Certified Robustness for ReLU Networks
In Deep Learning (Adversarial) 4
Tsui-Wei Weng · Huan Zhang · Hongge Chen · Zhao Song · Cho-Jui Hsieh · Luca Daniel · Duane Boning · Inderjit Dhillon
[ PDF] 
Oral
Thu Jul 12 07:50 AM -- 08:00 AM (PDT) @ A1
Importance Weighted Transfer of Samples in Reinforcement Learning
In Reinforcement Learning 11
Andrea Tirinzoni · Andrea Sessa · Matteo Pirotta · Marcello Restelli
[ PDF] 
Oral
Thu Jul 12 07:50 AM -- 08:00 AM (PDT) @ Victoria
High Performance Zero-Memory Overhead Direct Convolutions
In Deep Learning (Neural Network Architectures) 9
Jiyuan Zhang · Franz Franchetti · Tze Meng Low
[ PDF] 
Oral
Thu Jul 12 07:50 AM -- 08:00 AM (PDT) @ A3
Towards Binary-Valued Gates for Robust LSTM Training
In Natural Language and Speech Processing 1
Zhuohan Li · Di He · Fei Tian · Wei Chen · Tao Qin · Liwei Wang · Tie-Yan Liu
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:50 AM -- 08:00 AM (PDT) @ A9
Accelerating Natural Gradient with Higher-Order Invariance
In Optimization (Non-convex) 3
Yang Song · Jiaming Song · Stefano Ermon
[ PDF] 
Oral
Thu Jul 12 07:50 AM -- 08:00 AM (PDT) @ A5
Stochastic Proximal Algorithms for AUC Maximization
In Online Learning 2
Michael Natole Jr · Yiming Ying · Siwei Lyu
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:50 AM -- 08:00 AM (PDT) @ K11
Fast Maximization of Non-Submodular, Monotonic Functions on the Integer Lattice
In Optimization (Combinatorial) 3
Alan Kuhnle · J. Smith · Victoria Crawford · My T. Thai
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:50 AM -- 08:00 AM (PDT) @ A4
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam
In Deep Learning (Bayesian) 2
Mohammad Emtiyaz Khan · Didrik Nielsen · Voot Tangkaratt · Wu Lin · Yarin Gal · Akash Srivastava
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:50 AM -- 08:00 AM (PDT) @ K1
Understanding Generalization and Optimization Performance of Deep CNNs
In Deep Learning (Theory) 5
Pan Zhou · Jiashi Feng
[ PDF]  [ Video] 
Oral
Thu Jul 12 07:50 AM -- 08:00 AM (PDT) @ A7
LaVAN: Localized and Visible Adversarial Noise
In Deep Learning (Adversarial) 4
Danny Karmon · Daniel Zoran · Yoav Goldberg
[ PDF] 
Oral
Thu Jul 12 07:50 AM -- 08:00 AM (PDT) @ A6
Binary Classification with Karmic, Threshold-Quasi-Concave Metrics
In Statistical Learning Theory 4
Bowei Yan · Sanmi Koyejo · Kai Zhong · Pradeep Ravikumar
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:00 AM -- 08:20 AM (PDT) @ A3
Efficient Model-Based Deep Reinforcement Learning with Variational State Tabulation
In Reinforcement Learning 13
Dane Corneil · Wulfram Gerstner · Johanni Brea
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:00 AM -- 08:20 AM (PDT) @ A6
SAFFRON: an Adaptive Algorithm for Online Control of the False Discovery Rate
In Other Models and Methods 1
Aaditya Ramdas · Tijana Zrnic · Martin Wainwright · Michael Jordan
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:00 AM -- 08:20 AM (PDT) @ A9
Stochastic Wasserstein Barycenters
In Optimization (Non-convex) 4
Sebastian Claici · Edward Chien · Justin Solomon
[ PDF] 
Oral
Thu Jul 12 08:00 AM -- 08:20 AM (PDT) @ A5
Let’s be Honest: An Optimal No-Regret Framework for Zero-Sum Games
In Online Learning 3
Ehsan Asadi Kangarshahi · Ya-Ping Hsieh · Mehmet Fatih Sahin · Volkan Cevher
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:00 AM -- 08:20 AM (PDT) @ K1
Composable Planning with Attributes
In Transfer and Multi-Task Learning 2
Amy Zhang · Sainbayar Sukhbaatar · Adam Lerer · Arthur Szlam · Facebook Rob Fergus
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:00 AM -- 08:20 AM (PDT) @ A1
An Efficient, Generalized Bellman Update For Cooperative Inverse Reinforcement Learning
In Reinforcement Learning 12
Dhruv Malik · Malayandi Palaniappan · Jaime Fisac · Dylan Hadfield-Menell · Stuart Russell · Anca Dragan
[ PDF] 
Oral
Thu Jul 12 08:00 AM -- 08:20 AM (PDT) @ Victoria
ContextNet: Deep learning for Star Galaxy Classification
In Deep Learning (Neural Network Architectures) 10
Noble Kennamer · University of California David Kirkby · Alexander Ihler · University of California Francisco Javier Sanchez-Lopez
[ PDF] 
Oral
Thu Jul 12 08:00 AM -- 08:20 AM (PDT) @ A4
Neural Autoregressive Flows
In Deep Learning (Bayesian) 3
Chin-Wei Huang · David Krueger · Alexandre Lacoste · Aaron Courville
[ PDF] 
Oral
Thu Jul 12 08:00 AM -- 08:20 AM (PDT) @ K11
Representation Tradeoffs for Hyperbolic Embeddings
In Dimensionality Reduction 2
Frederic Sala · Christopher De Sa · Albert Gu · Christopher Re
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:00 AM -- 08:20 AM (PDT) @ A7
Synthesizing Programs for Images using Reinforced Adversarial Learning
In Deep Learning (Adversarial) 5
Iaroslav Ganin · Tejas Kulkarni · Igor Babuschkin · S. M. Ali Eslami · Oriol Vinyals
[ PDF] 
Oral
Thu Jul 12 08:20 AM -- 08:30 AM (PDT) @ A9
Learning Compact Neural Networks with Regularization
In Optimization (Non-convex) 4
Samet Oymak
[ PDF] 
Oral
Thu Jul 12 08:20 AM -- 08:30 AM (PDT) @ Victoria
Autoregressive Convolutional Neural Networks for Asynchronous Time Series
In Deep Learning (Neural Network Architectures) 10
Mikolaj Binkowski · Gautier Marti · Philippe Donnat
[ PDF] 
Oral
Thu Jul 12 08:20 AM -- 08:30 AM (PDT) @ A7
MAGAN: Aligning Biological Manifolds
In Deep Learning (Adversarial) 5
Matt Amodio · Smita Krishnaswamy
[ PDF] 
Oral
Thu Jul 12 08:20 AM -- 08:30 AM (PDT) @ A1
Fast Bellman Updates for Robust MDPs
In Reinforcement Learning 12
Chin Pang Ho · Marek Petrik · Wolfram Wiesemann
[ PDF] 
Oral
Thu Jul 12 08:20 AM -- 08:30 AM (PDT) @ A5
Weakly Consistent Optimal Pricing Algorithms in Repeated Posted-Price Auctions with Strategic Buyer
In Online Learning 3
Alexey Drutsa
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:20 AM -- 08:30 AM (PDT) @ A4
Distilling the Posterior in Bayesian Neural Networks
In Deep Learning (Bayesian) 3
Kuan-Chieh Wang · Paul Vicol · James Lucas · Li Gu · Roger Grosse · Richard Zemel
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:20 AM -- 08:30 AM (PDT) @ A6
Open Category Detection with PAC Guarantees
In Other Models and Methods 1
Si Liu · Risheek Garrepalli · Thomas Dietterich · Alan Fern · Dan Hendrycks
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:20 AM -- 08:40 AM (PDT) @ K11
Massively Parallel Algorithms and Hardness for Single-Linkage Clustering under $\ell_p$ Distances
In Dimensionality Reduction 2
Grigory Yaroslavtsev · Adithya Vadapalli
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:20 AM -- 08:40 AM (PDT) @ K1
Measuring abstract reasoning in neural networks
In Transfer and Multi-Task Learning 2
Adam Santoro · Feilx Hill · David GT Barrett · Ari S Morcos · Timothy Lillicrap
[ PDF]  [ PDF]  [ Video] 
Oral
Thu Jul 12 08:20 AM -- 08:40 AM (PDT) @ A3
Deep Variational Reinforcement Learning for POMDPs
In Reinforcement Learning 13
Maximilian Igl · Luisa Zintgraf · Tuan Anh Le · Frank Wood · Shimon Whiteson
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:30 AM -- 08:40 AM (PDT) @ A4
Bayesian Uncertainty Estimation for Batch Normalized Deep Networks
In Deep Learning (Bayesian) 3
Mattias Teye · Hossein Azizpour · Kevin Smith
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:30 AM -- 08:40 AM (PDT) @ Victoria
Hierarchical Multi-Label Classification Networks
In Deep Learning (Neural Network Architectures) 10
Jonatas Wehrmann · Ricardo Cerri · Rodrigo Barros
[ PDF] 
Oral
Thu Jul 12 08:30 AM -- 08:40 AM (PDT) @ A9
Riemannian Stochastic Recursive Gradient Algorithm with Retraction and Vector Transport and Its Convergence Analysis
In Optimization (Non-convex) 4
Hiroyuki Kasai · Hiroyuki Sato · Bamdev Mishra
[ PDF] 
Oral
Thu Jul 12 08:30 AM -- 08:40 AM (PDT) @ A7
Max-Mahalanobis Linear Discriminant Analysis Networks
In Deep Learning (Adversarial) 5
Tianyu Pang · Chao Du · Jun Zhu
[ PDF] 
Oral
Thu Jul 12 08:30 AM -- 08:40 AM (PDT) @ A1
Decoupling Gradient-Like Learning Rules from Representations
In Reinforcement Learning 12
Philip Thomas · Christoph Dann · Emma Brunskill
[ PDF] 
Oral
Thu Jul 12 08:30 AM -- 08:40 AM (PDT) @ A5
Self-Bounded Prediction Suffix Tree via Approximate String Matching
In Online Learning 3
Dongwoo Kim · Christian Walder
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:30 AM -- 08:40 AM (PDT) @ A6
Unbiased Objective Estimation in Predictive Optimization
In Other Models and Methods 1
Shinji Ito · Akihiro Yabe · Ryohei Fujimaki
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:40 AM -- 08:50 AM (PDT) @ A6
Goodness-of-fit Testing for Discrete Distributions via Stein Discrepancy
In Other Models and Methods 1
Jiasen Yang · Qiang Liu · Vinayak A Rao · Jennifer Neville
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:40 AM -- 08:50 AM (PDT) @ A3
Recurrent Predictive State Policy Networks
In Reinforcement Learning 13
Ahmed Hefny · Zita Marinho · Wen Sun · Siddhartha Srinivasa · Geoff Gordon
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:40 AM -- 08:50 AM (PDT) @ A5
Spatio-temporal Bayesian On-line Changepoint Detection with Model Selection
In Online Learning 3
Jeremias Knoblauch · Theodoros Damoulas
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:40 AM -- 08:50 AM (PDT) @ A4
Noisy Natural Gradient as Variational Inference
In Deep Learning (Bayesian) 3
Guodong Zhang · Shengyang Sun · David Duvenaud · Roger Grosse
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:40 AM -- 08:50 AM (PDT) @ K1
GradNorm: Gradient Normalization for Adaptive Loss Balancing in Deep Multitask Networks
In Transfer and Multi-Task Learning 2
Zhao Chen · Vijay Badrinarayanan · Chen-Yu Lee · Andrew Rabinovich
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:40 AM -- 08:50 AM (PDT) @ Victoria
Nonparametric variable importance using an augmented neural network with multi-task learning
In Deep Learning (Neural Network Architectures) 10
Jean Feng · Brian Williamson · Noah Simon · Marco Carone
[ PDF] 
Oral
Thu Jul 12 08:40 AM -- 08:50 AM (PDT) @ A9
Low-Rank Riemannian Optimization on Positive Semidefinite Stochastic Matrices with Applications to Graph Clustering
In Optimization (Non-convex) 4
Ahmed Douik · Babak Hassibi
[ PDF] 
Oral
Thu Jul 12 08:40 AM -- 08:50 AM (PDT) @ A7
Adversarial Time-to-Event Modeling
In Deep Learning (Adversarial) 5
Paidamoyo Chapfuwa · Chenyang Tao · Chunyuan Li · Courtney Page · Benjamin Goldstein · Lawrence Carin · Ricardo Henao
[ PDF] 
Oral
Thu Jul 12 08:40 AM -- 08:50 AM (PDT) @ A1
PIPPS: Flexible Model-Based Policy Search Robust to the Curse of Chaos
In Reinforcement Learning 12
Paavo Parmas · Carl E Rasmussen · Jan Peters · Kenji Doya
[ PDF] 
Oral
Thu Jul 12 08:40 AM -- 08:50 AM (PDT) @ K11
Local Density Estimation in High Dimensions
In Dimensionality Reduction 2
Xian Wu · Moses Charikar · Vishnu Natchu
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:50 AM -- 09:00 AM (PDT) @ A1
Discovering and Removing Exogenous State Variables and Rewards for Reinforcement Learning
In Reinforcement Learning 12
Thomas Dietterich · George Trimponias · Zhitang Chen
[ PDF] 
Oral
Thu Jul 12 08:50 AM -- 09:00 AM (PDT) @ K1
Explicit Inductive Bias for Transfer Learning with Convolutional Networks
In Transfer and Multi-Task Learning 2
Xuhong LI · Yves Grandvalet · Franck Davoine
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:50 AM -- 09:00 AM (PDT) @ A9
Graphical Nonconvex Optimization via an Adaptive Convex Relaxation
In Optimization (Non-convex) 4
Qiang Sun · Kean Ming Tan · Han Liu · Tong Zhang
[ PDF] 
Oral
Thu Jul 12 08:50 AM -- 09:00 AM (PDT) @ K11
Improving Sign Random Projections With Additional Information
In Dimensionality Reduction 2
Keegan Kang · Wei Pin Wong
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:50 AM -- 09:00 AM (PDT) @ A5
Learning Localized Spatio-Temporal Models From Streaming Data
In Online Learning 3
Muhammad Osama · Dave Zachariah · Thomas Schön
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:50 AM -- 09:00 AM (PDT) @ A6
Towards Black-box Iterative Machine Teaching
In Other Models and Methods 1
Weiyang Liu · Bo Dai · Xingguo Li · Zhen Liu · James Rehg · Le Song
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:50 AM -- 09:00 AM (PDT) @ A7
Reinforcing Adversarial Robustness using Model Confidence Induced by Adversarial Training
In Deep Learning (Adversarial) 5
Xi Wu · Wooyeong Jang · Jiefeng Chen · Lingjiao Chen · Somesh Jha
[ PDF] 
Oral
Thu Jul 12 08:50 AM -- 09:00 AM (PDT) @ A3
Regret Minimization for Partially Observable Deep Reinforcement Learning
In Reinforcement Learning 13
Peter Jin · EECS Kurt Keutzer · Sergey Levine
[ PDF]  [ Video] 
Oral
Thu Jul 12 08:50 AM -- 09:00 AM (PDT) @ A4
Structured Variational Learning of Bayesian Neural Networks with Horseshoe Priors
In Deep Learning (Bayesian) 3
Soumya Ghosh · Jiayu Yao · Finale Doshi-Velez
[ PDF] 
Oral
Thu Jul 12 08:50 AM -- 09:00 AM (PDT) @ Victoria
Knowledge Transfer with Jacobian Matching
In Deep Learning (Neural Network Architectures) 10
Suraj Srinivas · Francois Fleuret
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #1
Large-Scale Sparse Inverse Covariance Estimation via Thresholding and Max-Det Matrix Completion
In Posters Thu
Richard Zhang · Salar Fattahi · Somayeh Sojoudi
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #2
Robust and Scalable Models of Microbiome Dynamics
In Posters Thu
Travis Gibson · Georg Gerber
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #3
Explicit Inductive Bias for Transfer Learning with Convolutional Networks
In Posters Thu
Xuhong LI · Yves Grandvalet · Franck Davoine
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #4
GradNorm: Gradient Normalization for Adaptive Loss Balancing in Deep Multitask Networks
In Posters Thu
Zhao Chen · Vijay Badrinarayanan · Chen-Yu Lee · Andrew Rabinovich
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #5
Optimizing the Latent Space of Generative Networks
In Posters Thu
Piotr Bojanowski · Armand Joulin · David Lopez-Paz · Arthur Szlam
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #6
Theoretical Analysis of Image-to-Image Translation with Adversarial Learning
In Posters Thu
Xudong Pan · Mi Zhang · Daizong Ding
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #7
Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor
In Posters Thu
Tuomas Haarnoja · Aurick Zhou · Pieter Abbeel · Sergey Levine
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #8
PIPPS: Flexible Model-Based Policy Search Robust to the Curse of Chaos
In Posters Thu
Paavo Parmas · Carl E Rasmussen · Jan Peters · Kenji Doya
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #9
Probabilistic Recurrent State-Space Models
In Posters Thu
Andreas Doerr · Christian Daniel · Martin Schiegg · Duy Nguyen-Tuong · Stefan Schaal · Marc Toussaint · Sebastian Trimpe
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #10
Structured Variationally Auto-encoded Optimization
In Posters Thu
Xiaoyu Lu · Javier González · Zhenwen Dai · Neil Lawrence
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #11
A Robust Approach to Sequential Information Theoretic Planning
In Posters Thu
Sue Zheng · Jason Pacheco · John Fisher
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #12
Error Estimation for Randomized Least-Squares Algorithms via the Bootstrap
In Posters Thu
Miles Lopes · Shusen Wang · Michael Mahoney
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #13
Distributed Asynchronous Optimization with Unbounded Delays: How Slow Can You Go?
In Posters Thu
Zhengyuan Zhou · Panayotis Mertikopoulos · Nicholas Bambos · Peter Glynn · Yinyu Ye · Li-Jia Li · Li Fei-Fei
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #14
Error Compensated Quantized SGD and its Applications to Large-scale Distributed Optimization
In Posters Thu
Jiaxiang Wu · Weidong Huang · Junzhou Huang · Tong Zhang
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #15
Low-Rank Riemannian Optimization on Positive Semidefinite Stochastic Matrices with Applications to Graph Clustering
In Posters Thu
Ahmed Douik · Babak Hassibi
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #16
Dissecting Adam: The Sign, Magnitude and Variance of Stochastic Gradients
In Posters Thu
Lukas Balles · Philipp Hennig
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #17
Discovering and Removing Exogenous State Variables and Rewards for Reinforcement Learning
In Posters Thu
Thomas Dietterich · George Trimponias · Zhitang Chen
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #18
Differentially Private Database Release via Kernel Mean Embeddings
In Posters Thu
Matej Balog · Ilya Tolstikhin · Bernhard Schölkopf
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #19
Extracting Automata from Recurrent Neural Networks Using Queries and Counterexamples
In Posters Thu
Gail Weiss · Yoav Goldberg · Eran Yahav
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #20
Neural Dynamic Programming for Musical Self Similarity
In Posters Thu
Christian Walder · Dongwoo Kim
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #21
Learning long term dependencies via Fourier recurrent units
In Posters Thu
Jiong Zhang · Yibo Lin · Zhao Song · Inderjit Dhillon
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #22
Autoregressive Convolutional Neural Networks for Asynchronous Time Series
In Posters Thu
Mikolaj Binkowski · Gautier Marti · Philippe Donnat
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #23
Efficient Model-Based Deep Reinforcement Learning with Variational State Tabulation
In Posters Thu
Dane Corneil · Wulfram Gerstner · Johanni Brea
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #24
Regret Minimization for Partially Observable Deep Reinforcement Learning
In Posters Thu
Peter Jin · EECS Kurt Keutzer · Sergey Levine
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #25
Goodness-of-fit Testing for Discrete Distributions via Stein Discrepancy
In Posters Thu
Jiasen Yang · Qiang Liu · Vinayak A Rao · Jennifer Neville
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #26
Unbiased Objective Estimation in Predictive Optimization
In Posters Thu
Shinji Ito · Akihiro Yabe · Ryohei Fujimaki
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #27
Ultra Large-Scale Feature Selection using Count-Sketches
In Posters Thu
Amirali Aghazadeh · Ryan Spring · Daniel LeJeune · Gautam Dasarathy · Anshumali Shrivastava · Richard Baraniuk
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #28
Matrix Norms in Data Streams: Faster, Multi-Pass and Row-Order
In Posters Thu
Vladimir Braverman · Stephen Chestnut · Robert Krauthgamer · Yi Li · David Woodruff · Lin Yang
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #29
Can Deep Reinforcement Learning Solve Erdos-Selfridge-Spencer Games?
In Posters Thu
Maithra Raghu · Alexander Irpan · Jacob Andreas · Bobby Kleinberg · Quoc Le · Jon Kleinberg
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #30
The Mirage of Action-Dependent Baselines in Reinforcement Learning
In Posters Thu
George Tucker · Surya Bhupatiraju · Shixiang Gu · Richard E Turner · Zoubin Ghahramani · Sergey Levine
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #31
Composite Marginal Likelihood Methods for Random Utility Models
In Posters Thu
Zhibing Zhao · Lirong Xia
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #32
Ranking Distributions based on Noisy Sorting
In Posters Thu
Adil El Mesaoudi-Paul · Eyke Hüllermeier · Robert Busa-Fekete
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #33
DICOD: Distributed Convolutional Coordinate Descent for Convolutional Sparse Coding
In Posters Thu
Thomas Moreau · Laurent Oudre · Nicolas Vayatis
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #34
Exploring Hidden Dimensions in Accelerating Convolutional Neural Networks
In Posters Thu
Zhihao Jia · Sina Lin · Charles Qi · Alex Aiken
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #35
Deep Models of Interactions Across Sets
In Posters Thu
Jason Hartford · Devon Graham · Kevin Leyton-Brown · Siamak Ravanbakhsh
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #36
ContextNet: Deep learning for Star Galaxy Classification
In Posters Thu
Noble Kennamer · University of California David Kirkby · Alexander Ihler · University of California Francisco Javier Sanchez-Lopez
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #37
First Order Generative Adversarial Networks
In Posters Thu
Calvin Seward · Thomas Unterthiner · Urs M Bergmann · Nikolay Jetchev · Sepp Hochreiter
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #38
Max-Mahalanobis Linear Discriminant Analysis Networks
In Posters Thu
Tianyu Pang · Chao Du · Jun Zhu
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #39
Learning Maximum-A-Posteriori Perturbation Models for Structured Prediction in Polynomial Time
In Posters Thu
Asish Ghoshal · Jean Honorio
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #40
Structured Output Learning with Abstention: Application to Accurate Opinion Prediction
In Posters Thu
Alexandre Garcia · Telecom-ParisTech Chloé Clavel · Slim Essid · Florence d'Alche-Buc
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #41
SBEED: Convergent Reinforcement Learning with Nonlinear Function Approximation
In Posters Thu
Bo Dai · Albert Shaw · Lihong Li · Lin Xiao · Niao He · Zhen Liu · Jianshu Chen · Le Song
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #42
Smoothed Action Value Functions for Learning Gaussian Policies
In Posters Thu
Ofir Nachum · Mohammad Norouzi · George Tucker · Dale Schuurmans
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #43
Towards End-to-End Prosody Transfer for Expressive Speech Synthesis with Tacotron
In Posters Thu
RJ Skerry-Ryan · Eric Battenberg · Ying Xiao · Yuxuan Wang · Daisy Stanton · Joel Shor · Ron Weiss · Robert Clark · Rif Saurous
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #44
Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis
In Posters Thu
Yuxuan Wang · Daisy Stanton · Yu Zhang · RJ-Skerry Ryan · Eric Battenberg · Joel Shor · Ying Xiao · Ye Jia · Fei Ren · Rif Saurous
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #45
AutoPrognosis: Automated Clinical Prognostic Modeling via Bayesian Optimization with Structured Kernel Learning
In Posters Thu
Ahmed M. Alaa · Mihaela van der Schaar
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #46
TAPAS: Tricks to Accelerate (encrypted) Prediction As a Service
In Posters Thu
Amartya Sanyal · Matt Kusner · Adria Gascon · Varun Kanade
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #47
End-to-End Learning for the Deep Multivariate Probit Model
In Posters Thu
Di Chen · Yexiang Xue · Carla Gomes
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #48
Differentiable Dynamic Programming for Structured Prediction and Attention
In Posters Thu
Arthur Mensch · Mathieu Blondel
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #49
Optimal Distributed Learning with Multi-pass Stochastic Gradient Methods
In Posters Thu
Junhong Lin · Volkan Cevher
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #50
Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates
In Posters Thu
Dong Yin · Yudong Chen · Kannan Ramchandran · Peter Bartlett
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #51
SQL-Rank: A Listwise Approach to Collaborative Ranking
In Posters Thu
LIWEI WU · Cho-Jui Hsieh · University of California James Sharpnack
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #52
Extreme Learning to Rank via Low Rank Assumption
In Posters Thu
Minhao Cheng · Ian Davidson · Cho-Jui Hsieh
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #53
Adversarial Attack on Graph Structured Data
In Posters Thu
Hanjun Dai · Hui Li · Tian Tian · Xin Huang · Lin Wang · Jun Zhu · Le Song
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #54
Reinforcing Adversarial Robustness using Model Confidence Induced by Adversarial Training
In Posters Thu
Xi Wu · Wooyeong Jang · Jiefeng Chen · Lingjiao Chen · Somesh Jha
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #55
Closed-form Marginal Likelihood in Gamma-Poisson Matrix Factorization
In Posters Thu
Louis Filstroff · Alberto Lumbreras · Cedric Fevotte
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #56
Learning Binary Latent Variable Models: A Tensor Eigenpair Approach
In Posters Thu
Ariel Jaffe · Roi Weiss · Boaz Nadler · Shai Carmi · Yuval Kluger
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #57
Thompson Sampling for Combinatorial Semi-Bandits
In Posters Thu
Siwei Wang · Wei Chen
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #58
Let’s be Honest: An Optimal No-Regret Framework for Zero-Sum Games
In Posters Thu
Ehsan Asadi Kangarshahi · Ya-Ping Hsieh · Mehmet Fatih Sahin · Volkan Cevher
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #59
Deep Asymmetric Multi-task Feature Learning
In Posters Thu
Hae Beom Lee · Eunho Yang · Sung Ju Hwang
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #60
Learn from Your Neighbor: Learning Multi-modal Mappings from Sparse Annotations
In Posters Thu
Ashwin Kalyan · Stefan Lee · Anitha Kannan · Dhruv Batra
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #61
Stein Variational Message Passing for Continuous Graphical Models
In Posters Thu
Dilin Wang · Zhe Zeng · Qiang Liu
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #62
Discrete-Continuous Mixtures in Probabilistic Programming: Generalized Semantics and Inference Algorithms
In Posters Thu
Yi Wu · Siddharth Srivastava · Nicholas Hay · Simon Du · Stuart Russell
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #63
Towards Binary-Valued Gates for Robust LSTM Training
In Posters Thu
Zhuohan Li · Di He · Fei Tian · Wei Chen · Tao Qin · Liwei Wang · Tie-Yan Liu
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #64
Fitting New Speakers Based on a Short Untranscribed Sample
In Posters Thu
Eliya Nachmani · Adam Polyak · Yaniv Taigman · Lior Wolf
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #65
Stochastic Variance-Reduced Policy Gradient
In Posters Thu
Matteo Papini · Damiano Binaghi · Giuseppe Canonaco · Matteo Pirotta · Marcello Restelli
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #66
Convergent Tree Backup and Retrace with Function Approximation
In Posters Thu
Ahmed Touati · Pierre-Luc Bacon · Doina Precup · Pascal Vincent
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #67
Alternating Randomized Block Coordinate Descent
In Posters Thu
Jelena Diakonikolas · Orecchia Lorenzo
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #68
Shampoo: Preconditioned Stochastic Tensor Optimization
In Posters Thu
Vineet Gupta · Tomer Koren · Yoram Singer
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #69
Stochastic Wasserstein Barycenters
In Posters Thu
Sebastian Claici · Edward Chien · Justin Solomon
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #70
Accelerating Natural Gradient with Higher-Order Invariance
In Posters Thu
Yang Song · Jiaming Song · Stefano Ermon
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #71
Learning unknown ODE models with Gaussian processes
In Posters Thu
Markus Heinonen · Cagatay Yildiz · Henrik Mannerström · Jukka Intosalmi · Harri Lähdesmäki
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #72
Constraining the Dynamics of Deep Probabilistic Models
In Posters Thu
Marco Lorenzi · Maurizio Filippone
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #73
Fast Decoding in Sequence Models Using Discrete Latent Variables
In Posters Thu
Lukasz Kaiser · Samy Bengio · Aurko Roy · Ashish Vaswani · Niki Parmar · Jakob Uszkoreit · Noam Shazeer
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #74
High Performance Zero-Memory Overhead Direct Convolutions
In Posters Thu
Jiyuan Zhang · Franz Franchetti · Tze Meng Low
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #75
Approximate Leave-One-Out for Fast Parameter Tuning in High Dimensions
In Posters Thu
Shuaiwen Wang · Wenda Zhou · Haihao Lu · Arian Maleki · Vahab Mirrokni
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #76
Improved large-scale graph learning through ridge spectral sparsification
In Posters Thu
Daniele Calandriello · Alessandro Lazaric · Ioannis Koutis · Michal Valko
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #77
Distilling the Posterior in Bayesian Neural Networks
In Posters Thu
Kuan-Chieh Wang · Paul Vicol · James Lucas · Li Gu · Roger Grosse · Richard Zemel
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #78
Scalable approximate Bayesian inference for particle tracking data
In Posters Thu
Ruoxi Sun · Department of Statistics Liam Paninski
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #79
Weakly Consistent Optimal Pricing Algorithms in Repeated Posted-Price Auctions with Strategic Buyer
In Posters Thu
Alexey Drutsa
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #80
Practical Contextual Bandits with Regression Oracles
In Posters Thu
Dylan Foster · Alekh Agarwal · Miroslav Dudik · Haipeng Luo · Robert Schapire
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #81
Stochastic Variance-Reduced Hamilton Monte Carlo Methods
In Posters Thu
Difan Zou · Pan Xu · Quanquan Gu
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #82
Asynchronous Stochastic Quasi-Newton MCMC for Non-Convex Optimization
In Posters Thu
Umut Simsekli · Cagatay Yildiz · Thanh Huy Nguyen · Ali Taylan Cemgil · Gaël RICHARD
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #83
GAIN: Missing Data Imputation using Generative Adversarial Nets
In Posters Thu
Jinsung Yoon · James Jordon · Mihaela van der Schaar
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #84
Synthesizing Programs for Images using Reinforced Adversarial Learning
In Posters Thu
Iaroslav Ganin · Tejas Kulkarni · Igor Babuschkin · S. M. Ali Eslami · Oriol Vinyals
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #85
Geometry Score: A Method For Comparing Generative Adversarial Networks
In Posters Thu
Valentin Khrulkov · Ivan Oseledets
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #86
Addressing Function Approximation Error in Actor-Critic Methods
In Posters Thu
Scott Fujimoto · Herke van Hoof · David Meger
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #87
Fast Bellman Updates for Robust MDPs
In Posters Thu
Chin Pang Ho · Marek Petrik · Wolfram Wiesemann
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #88
Configurable Markov Decision Processes
In Posters Thu
Alberto Maria Metelli · Mirco Mutti · Marcello Restelli
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #89
Prediction Rule Reshaping
In Posters Thu
Matt Bonakdarpour · Sabyasachi Chatterjee · Rina Barber · John Lafferty
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #90
Dimensionality-Driven Learning with Noisy Labels
In Posters Thu
Xingjun Ma · Yisen Wang · Michael E. Houle · Shuo Zhou · Sarah Erfani · Shutao Xia · Sudanthi Wijewickrema · James Bailey
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #91
Learning Memory Access Patterns
In Posters Thu
Milad Hashemi · Kevin Swersky · Jamie Smith · Grant Ayers · Heiner Litz · Jichuan Chang · Christos Kozyrakis · Parthasarathy Ranganathan
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #92
Geodesic Convolutional Shape Optimization
In Posters Thu
Pierre Baque · Edoardo Remelli · Francois Fleuret · EPFL Pascal Fua
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #93
Visualizing and Understanding Atari Agents
In Posters Thu
Samuel Greydanus · Anurag Koul · Jonathan Dodge · Alan Fern
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #94
An Efficient, Generalized Bellman Update For Cooperative Inverse Reinforcement Learning
In Posters Thu
Dhruv Malik · Malayandi Palaniappan · Jaime Fisac · Dylan Hadfield-Menell · Stuart Russell · Anca Dragan
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #95
Is Generator Conditioning Causally Related to GAN Performance?
In Posters Thu
Augustus Odena · Jacob Buckman · Catherine Olsson · Tom B Brown · Christopher Olah · Colin Raffel · Ian Goodfellow
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #96
K-Beam Minimax: Efficient Optimization for Deep Adversarial Learning
In Posters Thu
Jihun Hamm · Yung-Kyun Noh
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #97
Inductive Two-Layer Modeling with Parametric Bregman Transfer
In Posters Thu
Vignesh Ganapathiraman · Zhan Shi · Xinhua Zhang · Yaoliang Yu
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #98
Does Distributionally Robust Supervised Learning Give Robust Classifiers?
In Posters Thu
Weihua Hu · Gang Niu · Issei Sato · Masashi Sugiyama
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #99
Understanding Generalization and Optimization Performance of Deep CNNs
In Posters Thu
Pan Zhou · Jiashi Feng
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #100
The Multilinear Structure of ReLU Networks
In Posters Thu
Thomas Laurent · James von Brecht
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #101
Parallel and Streaming Algorithms for K-Core Decomposition
In Posters Thu
Hossein Esfandiari · Silvio Lattanzi · Vahab Mirrokni
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #102
Fast Approximate Spectral Clustering for Dynamic Networks
In Posters Thu
Lionel Martin · Andreas Loukas · Pierre Vandergheynst
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #103
Gradient Descent Learns One-hidden-layer CNN: Don't be Afraid of Spurious Local Minima
In Posters Thu
Simon Du · Jason Lee · Yuandong Tian · Aarti Singh · Barnabás Póczos
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #104
Neural Networks Should Be Wide Enough to Learn Disconnected Decision Regions
In Posters Thu
Quynh Nguyen · Mahesh Mukkamala · Matthias Hein
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #105
Greed is Still Good: Maximizing Monotone Submodular+Supermodular (BP) Functions
In Posters Thu
Wenruo Bai · Jeff Bilmes
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #106
Black-box Adversarial Attacks with Limited Queries and Information
In Posters Thu
Andrew Ilyas · Logan Engstrom · Anish Athalye · Jessy Lin
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #107
Using Inherent Structures to design Lean 2-layer RBMs
In Posters Thu
Abhishek Bansal · Abhinav Anand · Chiranjib Bhattacharyya
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #108
Not to Cry Wolf: Distantly Supervised Multitask Learning in Critical Care
In Posters Thu
Patrick Schwab · Emanuela Keller · Carl Muroi · David J. Mack · Christian Strässle · Walter Karlen
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #109
Composable Planning with Attributes
In Posters Thu
Amy Zhang · Sainbayar Sukhbaatar · Adam Lerer · Arthur Szlam · Facebook Rob Fergus
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #110
Measuring abstract reasoning in neural networks
In Posters Thu
Adam Santoro · Feilx Hill · David GT Barrett · Ari S Morcos · Timothy Lillicrap
[ PDF]  [ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #111
Projection-Free Online Optimization with Stochastic Gradient: From Convexity to Submodularity
In Posters Thu
Lin Chen · Christopher Harshaw · Hamed Hassani · Amin Karbasi
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #112
Self-Bounded Prediction Suffix Tree via Approximate String Matching
In Posters Thu
Dongwoo Kim · Christian Walder
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #113
MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted Labels
In Posters Thu
Lu Jiang · Zhengyuan Zhou · Thomas Leung · Li-Jia Li · Li Fei-Fei
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #114
Curriculum Learning by Transfer Learning: Theory and Experiments with Deep Networks
In Posters Thu
Daphna Weinshall · Gad A Cohen · Dan Amir
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #115
Composite Functional Gradient Learning of Generative Adversarial Models
In Posters Thu
Rie Johnson · Tong Zhang
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #116
LaVAN: Localized and Visible Adversarial Noise
In Posters Thu
Danny Karmon · Daniel Zoran · Yoav Goldberg
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #117
Approximation Guarantees for Adaptive Sampling
In Posters Thu
Eric Balkanski · Yaron Singer
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #118
Constrained Interacting Submodular Groupings
In Posters Thu
Andrew Cotter · Mahdi Milani Fard · Seungil You · Maya Gupta · Jeff Bilmes
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #119
Residual Unfairness in Fair Machine Learning from Prejudiced Data
In Posters Thu
Nathan Kallus · Angela Zhou
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #120
Adversarial Regression with Multiple Learners
In Posters Thu
Liang Tong · Sixie Yu · Scott Alfeld · Yevgeniy Vorobeychik
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #121
Representation Tradeoffs for Hyperbolic Embeddings
In Posters Thu
Frederic Sala · Christopher De Sa · Albert Gu · Christopher Re
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #122
Improving Sign Random Projections With Additional Information
In Posters Thu
Keegan Kang · Wei Pin Wong
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #123
Bandits with Delayed, Aggregated Anonymous Feedback
In Posters Thu
Ciara Pike-Burke · Shipra Agrawal · Csaba Szepesvari · Steffen Grünewälder
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #124
Make the Minority Great Again: First-Order Regret Bound for Contextual Bandits
In Posters Thu
Zeyuan Allen-Zhu · Sebastien Bubeck · Yuanzhi Li
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #125
Learning Policy Representations in Multiagent Systems
In Posters Thu
Aditya Grover · Maruan Al-Shedivat · Jayesh K. Gupta · Yura Burda · Harrison Edwards
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #126
Learning to Coordinate with Coordination Graphs in Repeated Single-Stage Multi-Agent Decision Problems
In Posters Thu
Eugenio Bargiacchi · Timothy Verstraeten · Diederik Roijers · Ann Nowé · Hado van Hasselt
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #127
Beyond Finite Layer Neural Networks: Bridging Deep Architectures and Numerical Differential Equations
In Posters Thu
Yiping Lu · Aoxiao Zhong · Quanzheng Li · Bin Dong
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #128
Compressing Neural Networks using the Variational Information Bottelneck
In Posters Thu
Bin Dai · Chen Zhu · Baining Guo · David Wipf
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #129
Scalable Bilinear Pi Learning Using State and Action Features
In Posters Thu
Yichen Chen · Lihong Li · Mengdi Wang
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #130
Time Limits in Reinforcement Learning
In Posters Thu
Fabio Pardo · Arash Tavakoli · Vitaly Levdik · Petar Kormushev
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #131
Semi-Supervised Learning on Data Streams via Temporal Label Propagation
In Posters Thu
Tal Wagner · Sudipto Guha · Shiva Kasiviswanathan · Nina Mishra
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #132
Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval and Matrix Completion
In Posters Thu
Cong Ma · Kaizheng Wang · Yuejie Chi · Yuxin Chen
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #133
A Fast and Scalable Joint Estimator for Integrating Additional Knowledge in Learning Multiple Related Sparse Gaussian Graphical Models
In Posters Thu
Beilun Wang · Arshdeep Sekhon · Yanjun Qi
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #134
Bucket Renormalization for Approximate Inference
In Posters Thu
Sungsoo Ahn · Michael Chertkov · Adrian Weller · Jinwoo Shin
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #135
Kernel Recursive ABC: Point Estimation with Intractable Likelihood
In Posters Thu
Takafumi Kajihara · Motonobu Kanagawa · Keisuke Yamazaki · Kenji Fukumizu
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #136
Modeling Others using Oneself in Multi-Agent Reinforcement Learning
In Posters Thu
Roberta Raileanu · Emily Denton · Arthur Szlam · Facebook Rob Fergus
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #137
Tropical Geometry of Deep Neural Networks
In Posters Thu
Liwen Zhang · Gregory Naisat · Lek-Heng Lim
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #138
Learning Dynamics of Linear Denoising Autoencoders
In Posters Thu
Arnu Pretorius · Steve Kroon · Herman Kamper
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #139
Nonparametric variable importance using an augmented neural network with multi-task learning
In Posters Thu
Jean Feng · Brian Williamson · Noah Simon · Marco Carone
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #140
Training Neural Machines with Trace-Based Supervision
In Posters Thu
Matthew Mirman · Dimitar Dimitrov · Pavle Djordjevic · Timon Gehr · Martin Vechev
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #141
Open Category Detection with PAC Guarantees
In Posters Thu
Si Liu · Risheek Garrepalli · Thomas Dietterich · Alan Fern · Dan Hendrycks
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #142
SAFFRON: an Adaptive Algorithm for Online Control of the False Discovery Rate
In Posters Thu
Aaditya Ramdas · Tijana Zrnic · Martin Wainwright · Michael Jordan
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #143
Learning Localized Spatio-Temporal Models From Streaming Data
In Posters Thu
Muhammad Osama · Dave Zachariah · Thomas Schön
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #144
Feasible Arm Identification
In Posters Thu
Julian Katz-Samuels · Clay Scott
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #145
Fast Maximization of Non-Submodular, Monotonic Functions on the Integer Lattice
In Posters Thu
Alan Kuhnle · J. Smith · Victoria Crawford · My T. Thai
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #146
Decentralized Submodular Maximization: Bridging Discrete and Continuous Settings
In Posters Thu
Aryan Mokhtari · Hamed Hassani · Amin Karbasi
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #147
Towards Fast Computation of Certified Robustness for ReLU Networks
In Posters Thu
Tsui-Wei Weng · Huan Zhang · Hongge Chen · Zhao Song · Cho-Jui Hsieh · Luca Daniel · Duane Boning · Inderjit Dhillon
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #148
A Two-Step Computation of the Exact GAN Wasserstein Distance
In Posters Thu
Huidong Liu · Xianfeng GU · Samaras Dimitris
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #149
Spatio-temporal Bayesian On-line Changepoint Detection with Model Selection
In Posters Thu
Jeremias Knoblauch · Theodoros Damoulas
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #150
Fast Stochastic AUC Maximization with $O(1/n)$-Convergence Rate
In Posters Thu
Mingrui Liu · Xiaoxuan Zhang · Zaiyi Chen · Xiaoyu Wang · Tianbao Yang
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #151
Accurate Uncertainties for Deep Learning Using Calibrated Regression
In Posters Thu
Volodymyr Kuleshov · Nathan Fenner · Stefano Ermon
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #152
Neural Autoregressive Flows
In Posters Thu
Chin-Wei Huang · David Krueger · Alexandre Lacoste · Aaron Courville
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #153
Probabilistic Boolean Tensor Decomposition
In Posters Thu
Tammo Rukat · Christopher Holmes · Christopher Yau
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #154
A Primal-Dual Analysis of Global Optimality in Nonconvex Low-Rank Matrix Recovery
In Posters Thu
Xiao Zhang · Lingxiao Wang · Yaodong Yu · Quanquan Gu
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #155
A Delay-tolerant Proximal-Gradient Algorithm for Distributed Learning
In Posters Thu
Konstantin Mishchenko · Franck Iutzeler · Jérôme Malick · Massih-Reza Amini
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #156
Randomized Block Cubic Newton Method
In Posters Thu
Nikita Doikov · Peter Richtarik
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #157
Massively Parallel Algorithms and Hardness for Single-Linkage Clustering under $\ell_p$ Distances
In Posters Thu
Grigory Yaroslavtsev · Adithya Vadapalli
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #158
Local Density Estimation in High Dimensions
In Posters Thu
Xian Wu · Moses Charikar · Vishnu Natchu
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #159
To Understand Deep Learning We Need to Understand Kernel Learning
In Posters Thu
Mikhail Belkin · Siyuan Ma · Soumik Mandal
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #160
Learning in Reproducing Kernel Kreı̆n Spaces
In Posters Thu
Dino Oglic · Thomas Gaertner
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #161
Functional Gradient Boosting based on Residual Network Perception
In Posters Thu
Atsushi Nitanda · Taiji Suzuki
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #162
Binary Classification with Karmic, Threshold-Quasi-Concave Metrics
In Posters Thu
Bowei Yan · Sanmi Koyejo · Kai Zhong · Pradeep Ravikumar
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #163
Characterizing Implicit Bias in Terms of Optimization Geometry
In Posters Thu
Suriya Gunasekar · Jason Lee · Daniel Soudry · Nati Srebro
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #164
prDeep: Robust Phase Retrieval with a Flexible Deep Network
In Posters Thu
Christopher Metzler · Phillip Schniter · Ashok Veeraraghavan · Richard Baraniuk
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #165
Adversarial Time-to-Event Modeling
In Posters Thu
Paidamoyo Chapfuwa · Chenyang Tao · Chunyuan Li · Courtney Page · Benjamin Goldstein · Lawrence Carin · Ricardo Henao
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #166
MAGAN: Aligning Biological Manifolds
In Posters Thu
Matt Amodio · Smita Krishnaswamy
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #167
Multicalibration: Calibration for the (Computationally-Identifiable) Masses
In Posters Thu
Ursula Hebert-Johnson · Michael Kim · Omer Reingold · Guy Rothblum
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #168
Improving the Privacy and Accuracy of ADMM-Based Distributed Algorithms
In Posters Thu
Xueru Zhang · Mohammad Mahdi Khalili · Mingyan Liu
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #169
PixelSNAIL: An Improved Autoregressive Generative Model
In Posters Thu
Xi Chen · Nikhil Mishra · Mostafa Rohaninejad · Pieter Abbeel
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #170
Focused Hierarchical RNNs for Conditional Sequence Processing
In Posters Thu
Rosemary Nan Ke · Konrad Zolna · Alessandro Sordoni · Zhouhan Lin · Adam Trischler · Yoshua Bengio · Joelle Pineau · Laurent Charlin · Christopher Pal
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #171
Noise2Noise: Learning Image Restoration without Clean Data
In Posters Thu
Jaakko Lehtinen · Jacob Munkberg · Jon Hasselgren · Samuli Laine · Tero Karras · Miika Aittala · Timo Aila
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #172
Learning to Reweight Examples for Robust Deep Learning
In Posters Thu
Mengye Ren · Wenyuan Zeng · Bin Yang · Raquel Urtasun
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #173
Policy and Value Transfer in Lifelong Reinforcement Learning
In Posters Thu
David Abel · Yuu Jinnai · Sophie Guo · George Konidaris · Michael L. Littman
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #174
GEP-PG: Decoupling Exploration and Exploitation in Deep Reinforcement Learning Algorithms
In Posters Thu
Cédric Colas · Olivier Sigaud · Pierre-Yves Oudeyer
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #175
A Hierarchical Latent Vector Model for Learning Long-Term Structure in Music
In Posters Thu
Adam Roberts · Jesse Engel · Colin Raffel · Curtis Hawthorne · Douglas Eck
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #176
Understanding the Loss Surface of Neural Networks for Binary Classification
In Posters Thu
SHIYU LIANG · Ruoyu Sun · Yixuan Li · R Srikant
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #177
Dynamical Isometry and a Mean Field Theory of RNNs: Gating Enables Signal Propagation in Recurrent Neural Networks
In Posters Thu
Minmin Chen · Jeffrey Pennington · Samuel Schoenholz
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #178
Reviving and Improving Recurrent Back-Propagation
In Posters Thu
Renjie Liao · Yuwen Xiong · Ethan Fetaya · Lisa Zhang · KiJung Yoon · Zachary S Pitkow · Raquel Urtasun · Richard Zemel
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #179
Riemannian Stochastic Recursive Gradient Algorithm with Retraction and Vector Transport and Its Convergence Analysis
In Posters Thu
Hiroyuki Kasai · Hiroyuki Sato · Bamdev Mishra
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #180
Learning Compact Neural Networks with Regularization
In Posters Thu
Samet Oymak
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #181
Investigating Human Priors for Playing Video Games
In Posters Thu
Rachit Dubey · Pulkit Agrawal · Deepak Pathak · Tom Griffiths · Alexei Efros
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #182
Decoupling Gradient-Like Learning Rules from Representations
In Posters Thu
Philip Thomas · Christoph Dann · Emma Brunskill
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #183
Invariance of Weight Distributions in Rectified MLPs
In Posters Thu
Susumu Tsuchida · Fred Roosta · Marcus Gallagher
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #184
Stronger Generalization Bounds for Deep Nets via a Compression Approach
In Posters Thu
Sanjeev Arora · Rong Ge · Behnam Neyshabur · Yi Zhang
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #185
Near Optimal Frequent Directions for Sketching Dense and Sparse Matrices
In Posters Thu
Zengfeng Huang
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #186
Loss Decomposition for Fast Learning in Large Output Spaces
In Posters Thu
En-Hsu Yen · Satyen Kale · Felix Xinnan Yu · Daniel Holtmann-Rice · Sanjiv Kumar · Pradeep Ravikumar
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #187
Stochastic Proximal Algorithms for AUC Maximization
In Posters Thu
Michael Natole Jr · Yiming Ying · Siwei Lyu
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #188
Accelerated Spectral Ranking
In Posters Thu
Arpit Agarwal · Prathamesh Patil · Shivani Agarwal
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #189
Decomposition of Uncertainty in Bayesian Deep Learning for Efficient and Risk-sensitive Learning
In Posters Thu
Stefan Depeweg · Jose Miguel Hernandez-Lobato · Finale Doshi-Velez · Steffen Udluft
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #190
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam
In Posters Thu
Mohammad Emtiyaz Khan · Didrik Nielsen · Voot Tangkaratt · Wu Lin · Yarin Gal · Akash Srivastava
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #191
Learning One Convolutional Layer with Overlapping Patches
In Posters Thu
Surbhi Goel · Adam Klivans · Raghu Meka
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #192
A Spline Theory of Deep Learning
In Posters Thu
Randall Balestriero · Richard Baraniuk
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #193
Structured Variational Learning of Bayesian Neural Networks with Horseshoe Priors
In Posters Thu
Soumya Ghosh · Jiayu Yao · Finale Doshi-Velez
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #194
Variational Bayesian dropout: pitfalls and fixes
In Posters Thu
Jiri Hron · Alexander Matthews · Zoubin Ghahramani
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #195
Adversarial Learning with Local Coordinate Coding
In Posters Thu
Jiezhang Cao · Yong Guo · Qingyao Wu · Chunhua Shen · Junzhou Huang · Mingkui Tan
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #196
Learning Representations and Generative Models for 3D Point Clouds
In Posters Thu
Panagiotis Achlioptas · Olga Diamanti · Ioannis Mitliagkas · Leonidas Guibas
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #197
Bayesian Uncertainty Estimation for Batch Normalized Deep Networks
In Posters Thu
Mattias Teye · Hossein Azizpour · Kevin Smith
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #198
Noisy Natural Gradient as Variational Inference
In Posters Thu
Guodong Zhang · Shengyang Sun · David Duvenaud · Roger Grosse
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #199
Deep Variational Reinforcement Learning for POMDPs
In Posters Thu
Maximilian Igl · Luisa Zintgraf · Tuan Anh Le · Frank Wood · Shimon Whiteson
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #200
Recurrent Predictive State Policy Networks
In Posters Thu
Ahmed Hefny · Zita Marinho · Wen Sun · Siddhartha Srinivasa · Geoff Gordon
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #201
The Mechanics of n-Player Differentiable Games
In Posters Thu
David Balduzzi · Sebastien Racaniere · James Martens · Jakob Foerster · Karl Tuyls · Thore Graepel
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #202
Improved Training of Generative Adversarial Networks Using Representative Features
In Posters Thu
Duhyeon Bang · Hyunjung Shim
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #203
Hierarchical Multi-Label Classification Networks
In Posters Thu
Jonatas Wehrmann · Ricardo Cerri · Rodrigo Barros
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #204
Knowledge Transfer with Jacobian Matching
In Posters Thu
Suraj Srinivas · Francois Fleuret
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #205
Towards Black-box Iterative Machine Teaching
In Posters Thu
Weiyang Liu · Bo Dai · Xingguo Li · Zhen Liu · James Rehg · Le Song
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #206
Improving the Gaussian Mechanism for Differential Privacy: Analytical Calibration and Optimal Denoising
In Posters Thu
Borja de Balle Pigem · Yu-Xiang Wang
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #207
Importance Weighted Transfer of Samples in Reinforcement Learning
In Posters Thu
Andrea Tirinzoni · Andrea Sessa · Matteo Pirotta · Marcello Restelli
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #208
Beyond the One-Step Greedy Approach in Reinforcement Learning
In Posters Thu
Yonathan Efroni · Gal Dalal · Bruno Scherrer · Shie Mannor
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #209
Optimization, fast and slow: optimally switching between local and Bayesian optimization
In Posters Thu
Mark McLeod · Stephen Roberts · Michael A Osborne
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #210
Batch Bayesian Optimization via Multi-objective Acquisition Ensemble for Automated Analog Circuit Design
In Posters Thu
Wenlong Lyu · Fan Yang · Changhao Yan · Dian Zhou · Xuan Zeng
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #211
Graphical Nonconvex Optimization via an Adaptive Convex Relaxation
In Posters Thu
Qiang Sun · Kean Ming Tan · Han Liu · Tong Zhang
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #212
Approximate message passing for amplitude based optimization
In Posters Thu
Junjie Ma · Ji Xu · Arian Maleki
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #213
Delayed Impact of Fair Machine Learning
In Posters Thu
Lydia T. Liu · Sarah Dean · Esther Rolf · Max Simchowitz · Moritz Hardt
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #214
Tempered Adversarial Networks
In Posters Thu
Mehdi S. M. Sajjadi · Giambattista Parascandolo · Arash Mehrjou · Bernhard Schölkopf
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #215
Fast Information-theoretic Bayesian Optimisation
In Posters Thu
Binxin Ru · Michael A Osborne · Mark Mcleod · Diego Granziol
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #216
Tight Regret Bounds for Bayesian Optimization in One Dimension
In Posters Thu
Jonathan Scarlett
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #217
Image Transformer
In Posters Thu
Niki Parmar · Ashish Vaswani · Jakob Uszkoreit · Lukasz Kaiser · Noam Shazeer · Alexander Ku · Dustin Tran
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #218
Kernelized Synaptic Weight Matrices
In Posters Thu
Lorenz Müller · Julien Martel · Giacomo Indiveri
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #219
A Distributed Second-Order Algorithm You Can Trust
In Posters Thu
Celestine Mendler-Dünner · Aurelien Lucchi · Matilde Gargiani · Yatao Bian · Thomas Hofmann · Martin Jaggi
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #220
On Acceleration with Noise-Corrupted Gradients
In Posters Thu
Michael Cohen · Jelena Diakonikolas · Orecchia Lorenzo
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #221
Gradient Coding from Cyclic MDS Codes and Expander Graphs
In Posters Thu
Netanel Raviv · Rashish Tandon · Alexandros Dimakis · Itzhak Tamo
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #222
Accelerating Greedy Coordinate Descent Methods
In Posters Thu
Haihao Lu · Robert Freund · Vahab Mirrokni
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #223
Finding Influential Training Samples for Gradient Boosted Decision Trees
In Posters Thu
Boris Sharchilev · Yury Ustinovskiy · Pavel Serdyukov · Maarten de Rijke
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #224
Improving Regression Performance with Distributional Losses
In Posters Thu
Ehsan Imani · Martha White
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #225
QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning
In Posters Thu
Tabish Rashid · Mikayel Samvelyan · Christian Schroeder · Gregory Farquhar · Jakob Foerster · Shimon Whiteson
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #226
Learning to Act in Decentralized Partially Observable MDPs
In Posters Thu
Jilles Dibangoye · Olivier Buffet
[ PDF] 
Poster
Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #227
Local Convergence Properties of SAGA/Prox-SVRG and Acceleration
In Posters Thu
Clarice Poon · Jingwei Liang · Carola-Bibiane Schönlieb
[ PDF] 
Break
Thu Jul 12 10:30 AM -- 11:00 AM (PDT) @ Hall B
Coffee Break
Break
Thu Jul 12 12:00 PM -- 01:30 PM (PDT)
Lunch - on your own
Break
Thu Jul 12 03:30 PM -- 04:00 PM (PDT) @ Hall B
Coffee Break
Break
Thu Jul 12 06:15 PM -- 07:15 PM (PDT) @ Hall B
Light Evening Snack
Workshop
Thu Jul 12 11:30 PM -- 09:00 AM (PDT) @ K23
31st International Workshop on Qualitative Reasoning (QR 2018)
Workshop
Thu Jul 12 11:30 PM -- 09:00 AM (PDT) @ K24
6th Goal Reasoning Workshop
Workshop
Thu Jul 12 11:30 PM -- 09:00 AM (PDT) @ T4
Computer Games Workshop
Workshop
Thu Jul 12 11:30 PM -- 09:00 AM (PDT) @ K12
FCA4AI 2018
Workshop
Thu Jul 12 11:30 PM -- 09:00 AM (PDT) @ B2
Joint Workshop on AI in Health (day 1)
Workshop
Thu Jul 12 11:30 PM -- 09:00 AM (PDT) @ B9
Linguistic and Cognitive Approaches To Dialog Agents (LaCATODA 2018)
Workshop
Thu Jul 12 11:30 PM -- 03:30 AM (PDT) @ K22
Tenth International Workshop Modelling and Reasoning in Context (MRC)
Workshop
Thu Jul 12 11:30 PM -- 09:00 AM (PDT) @ B3
The 3rd International workshop on biomedical informatics with optimization and machine learning (BOOM)
Workshop
Thu Jul 12 11:30 PM -- 09:00 AM (PDT) @ B5
The 3rd International Workshop on Knowledge Discovery in Healthcare Data
Workshop
Thu Jul 12 11:30 PM -- 09:00 AM (PDT) @ T3
Towards learning with limited labels: Equivariance, Invariance, and Beyond
Workshop
Thu Jul 12 11:30 PM -- 09:00 AM (PDT) @ K2
Fairness, Interpretability, and Explainability Federation of Workshops (day 1)
Workshop
Thu Jul 12 11:30 PM -- 09:00 AM (PDT) @ K16
Autonomy in Teams -- Joint Workshop on Sharing Autonomy in Human-Robot Interaction