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Invited Talk
Tue May 1st 09:00 -- 09:45 AM @ Exhibition Hall A
Augmenting Clinical Intellgence with Machine Intelligence
Suchi Saria
Oral
Tue May 1st 09:45 -- 10:00 AM @ Exhibition Hall A
Learning to Represent Programs with Graphs
Miltiadis Allamanis · Marc Brockschmidt · Mahmoud Khademi
Oral
Tue May 1st 10:00 -- 10:15 AM @ Exhibition Hall A
Neural Sketch Learning for Conditional Program Generation
Vijayaraghavan Murali · Letao Qi · Swarat Chaudhuri · Chris Jermaine
Oral
Tue May 1st 10:15 -- 10:30 AM @ Exhibition Hall A
Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality
Xingjun Ma · Bo Li · Yisen Wang · Sarah Erfani · Sudanthi Wijewickrema · Grant Schoenebeck · dawn song · Michael E Houle · James Bailey
Oral
Tue May 1st 10:30 -- 10:45 AM @ Exhibition Hall A
Certifying Some Distributional Robustness with Principled Adversarial Training
Aman Sinha · Hong Namkoong · John Duchi
Break
Tue May 1st 10:45 -- 11:00 AM @ Ballroom ABC
Coffee Break
Poster
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting level; 1,2,3 #1
Hierarchical Subtask Discovery with Non-Negative Matrix Factorization
Adam Earle · Andrew Saxe · Benjamin Rosman
Poster
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting level; 1,2,3 #2
A Simple Neural Attentive Meta-Learner
Nikhil Mishra · Mostafa Rohaninejad · Xi Chen · Pieter Abbeel
Poster
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting level; 1,2,3 #3
Dynamic Neural Program Embeddings for Program Repair
Ke Wang · Rishabh Singh · Zhendong Su
Poster
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting level; 1,2,3 #4
Stochastic Activation Pruning for Robust Adversarial Defense
Guneet S Dhillon · Kamyar Azizzadenesheli · Zachary Lipton · Jeremy Bernstein · Jean Kossaifi · Aran Khanna · anima anandkumar
Poster
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting level; 1,2,3 #5
Do GANs learn the distribution? Some Theory and Empirics
Sanjeev Arora · Andrej Risteski · Yi Zhang
Poster
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting level; 1,2,3 #6
Learning Parametric Closed-Loop Policies for Markov Potential Games
Sergio Valcarcel Macua · Javier Zazo · Santiago Zazo
Poster
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting level; 1,2,3 #7
Learning Approximate Inference Networks for Structured Prediction
Lifu Tu · Kevin Gimpel
Poster
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting level; 1,2,3 #8
Fidelity-Weighted Learning
Mostafa Dehghani · Arash Mehrjou · Stephan Gouws · Jaap Kamps · Bernhard Schoelkopf
Poster
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting level; 1,2,3 #9
HexaConv
Emiel Hoogeboom · Jorn Peters · Taco Cohen · Max Welling
Poster
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting level; 1,2,3 #10
On the Convergence of Adam and Beyond
Sashank Reddi · Satyen Kale · Sanjiv Kumar
Poster
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting level; 1,2,3 #11
Generalizing Across Domains via Cross-Gradient Training
Shiv Shankar · Vihari Piratla · Soumen Chakrabarti · Siddhartha Chaudhuri · Preethi Jyothi · Sunita Sarawagi
Poster
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting level; 1,2,3 #12
Understanding image motion with group representations
Andrew Jaegle · Stephen Phillips · Daphne Ippolito · Kostas Daniilidis
Poster
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting level; 1,2,3 #13
Matrix capsules with EM routing
Geoffrey E Hinton · Sara Sabour · Nicholas Frosst
Poster
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting level; 1,2,3 #14
Global Optimality Conditions for Deep Neural Networks
Chulhee Yun · Suvrit Sra · Ali Jadbabaie
Poster
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting level; 1,2,3 #15
A PAC-Bayesian Approach to Spectrally-Normalized Margin Bounds for Neural Networks
Behnam Neyshabur · Srinadh Bhojanapalli · Nathan Srebro
Poster
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting level; 1,2,3 #16
Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach
Tsui-Wei Weng · Huan Zhang · Pin-Yu Chen · Jinfeng Yi · Dong Su · Yupeng Gao · Cho-Jui Hsieh · Luca Daniel
Poster
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting level; 1,2,3 #17
Sobolev GAN
Youssef Mroueh · Chun-Liang Li · Tom Sercu · Anant Raj · Yu Cheng
Poster
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting level; 1,2,3 #18
Divide-and-Conquer Reinforcement Learning
Dibya Ghosh · Avi Singh · Aravind Rajeswaran · Vikash Kumar · Sergey Levine
Poster
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting level; 1,2,3 #19
i-RevNet: Deep Invertible Networks
Joern-Henrik Jacobsen · Arnold W Smeulders · Edouard Oyallon
Poster
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting level; 1,2,3 #20
Multi-View Data Generation Without View Supervision
Mickael Chen · Ludovic Denoyer · thierry artieres
Poster
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting level; 1,2,3 #21
Action-dependent Control Variates for Policy Optimization via Stein Identity
Hao Liu · Yihao Feng · Yi Mao · Dengyong Zhou · Jian Peng ·
Poster
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting level; 1,2,3 #22
Ask the Right Questions: Active Question Reformulation with Reinforcement Learning
Christian Buck · Jannis Bulian · Massimiliano Ciaramita · Wojciech Gajewski · Andrea Gesmundo · Neil Houlsby · Wei Wang.
Poster
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting level; 1,2,3 #23
Temporal Difference Models: Model-Free Deep RL for Model-Based Control
Vitchyr Pong · Shixiang Gu · Murtaza Dalal · Sergey Levine
Poster
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting level; 1,2,3 #24
Model-Ensemble Trust-Region Policy Optimization
Thanard Kurutach · Ignasi Clavera · Yan Duan · Aviv Tamar · Pieter Abbeel
Poster
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting level; 1,2,3 #25
Generating Wikipedia by Summarizing Long Sequences
Peter J Liu · Mohammad Saleh · Etienne Pot · Ben Goodrich · Ryan Sepassi · Lukasz Kaiser · Noam Shazeer
Poster
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting level; 1,2,3 #26
Neural Language Modeling by Jointly Learning Syntax and Lexicon
Yikang Shen · Zhouhan Lin · Chin-Wei Huang · Aaron Courville
Poster
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting level; 1,2,3 #27
Deep Autoencoding Gaussian Mixture Model for Unsupervised Anomaly Detection
Bo Zong · Qi Song · Martin Min · Wei Cheng · Cristian Lumezanu · Daeki Cho · Haifeng Chen
Poster
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting level; 1,2,3 #28
An efficient framework for learning sentence representations
Lajanugen Logeswaran · Honglak Lee
Poster
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting level; 1,2,3 #29
Latent Space Oddity: on the Curvature of Deep Generative Models
Georgios Arvanitidis · Lars K Hansen · Søren Hauberg
Poster
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting level; 1,2,3 #30
N2N learning: Network to Network Compression via Policy Gradient Reinforcement Learning
Anubhav Ashok · Nicholas Rhinehart · Fares Beainy · Kris M Kitani
Poster
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting level; 1,2,3 #31
Variational Message Passing with Structured Inference Networks
Wu Lin · Nicolas Daniel Hubacher · Mohammad Emtiyaz Khan
Poster
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting level; 1,2,3 #32
Emergence of Linguistic Communication from Referential Games with Symbolic and Pixel Input
Angeliki Lazaridou · Karl M Hermann · Karl Tuyls · Stephen Clark
Poster
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting level; 1,2,3 #33
SCAN: Learning Hierarchical Compositional Visual Concepts
Irina Higgins · Nicolas Sonnerat · Loic Matthey · Arka Pal · Christopher P Burgess · Matko Bošnjak · Murray Shanahan · Matthew Botvinick · · Alexander Lerchner
Poster
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting level; 1,2,3 #34
The Role of Minimal Complexity Functions in Unsupervised Learning of Semantic Mappings
Tomer Galanti · Lior Wolf · Sagie Benaim
Poster
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting level; 1,2,3 #35
Learning Sparse Latent Representations with the Deep Copula Information Bottleneck
Aleksander Wieczorek · Mario Wieser · Damian Murezzan · Volker Roth
Poster
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting level; 1,2,3 #36
Learning From Noisy Singly-labeled Data
Ashish Khetan · Zachary Lipton · anima anandkumar
Poster
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting level; 1,2,3 #37
Gaussian Process Behaviour in Wide Deep Neural Networks
Alexander Matthews · Jiri Hron · Mark Rowland · Richard E Turner · Zoubin Ghahramani
Poster
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting level; 1,2,3 #38
Critical Points of Linear Neural Networks: Analytical Forms and Landscape Properties
Yi Zhou · Yingbin Liang
Poster
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting level; 1,2,3 #39
Apprentice: Using Knowledge Distillation Techniques To Improve Low-Precision Network Accuracy
Asit Mishra · Debbie Marr
Poster
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting level; 1,2,3 #40
Wavelet Pooling for Convolutional Neural Networks
Travis Williams · Robert Li
Poster
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting level; 1,2,3 #41
Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality
Xingjun Ma · Bo Li · Yisen Wang · Sarah Erfani · Sudanthi Wijewickrema · Grant Schoenebeck · dawn song · Michael E Houle · James Bailey
Poster
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting level; 1,2,3 #42
Learning Intrinsic Sparse Structures within Long Short-Term Memory
Wei Wen · Yuxiong He · Samyam Rajbhandari · Minjia Zhang · Wenhan Wang · Fang Liu · Bin Hu · Yiran Chen · Hai Li
Workshop
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting Level 8 + 15 #1
Investigating Human Priors for Playing Video Games
Rachit Dubey · Pulkit Agrawal · Deepak Pathak · Alexei Efros · Thomas L Griffiths
Workshop
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting Level 8 + 15 #2
An Evaluation of Fisher Approximations Beyond Kronecker Factorization
César Laurent · Thomas George · Xavier Bouthillier · Nicolas Ballas · Pascal Vincent
Workshop
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting Level 8 + 15 #3
ChatPainter: Improving Text to Image Generation using Dialogue
Shikhar Sharma · Dendi Suhubdy · Vincent Michalski · Samira Ebrahimi Kahou · Yoshua Bengio
Workshop
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting Level 8 + 15 #4
Meta-Learning for Batch Mode Active Learning
Sachin Ravi · Hugo Larochelle
Workshop
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting Level 8 + 15 #5
Learning and Memorization
Satrajit Chatterjee
Workshop
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting Level 8 + 15 #6
Spatially Parallel Convolutions
Peter Jin · Boris Ginsburg · Kurt Keutzer
Workshop
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting Level 8 + 15 #7
Fast and Accurate Text Classification: Skimming, Rereading and Early Stopping
Keyi Yu · Yang Liu · Alex Schwing · Jian Peng
Workshop
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting Level 8 + 15 #8
Analysis of Cosmic Microwave Background with Deep Learning
Siyu He · Siamak Ravanbakhsh · Shirley Ho
Workshop
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting Level 8 + 15 #9
Monotonic models for real-time dynamic malware detection
Alexander Chistyakov · · Aleksandr Shevelev ·
Workshop
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting Level 8 + 15 #10
Nonlinear Acceleration of CNNs
Damien Scieur · Edouard Oyallon · Alexandre d'Aspremont · Francis Bach
Workshop
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting Level 8 + 15 #11
Decoupling Dynamics and Reward for Transfer Learning
Harsh Satija · Amy Zhang · Joelle Pineau
Workshop
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting Level 8 + 15 #12
Uncertainty Estimation via Stochastic Batch Normalization
Andrei Atanov · Arsenii Ashukha · Dmitry Molchanov · Kirill Neklyudov · Dmitry P. Vetrov
Workshop
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting Level 8 + 15 #13
Learning Efficient Tensor Representations with Ring Structure Networks
Qibin Zhao · Masashi Sugiyama · Longhao Yuan · Andrzej Cichocki
Workshop
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting Level 8 + 15 #14
To Prune, or Not to Prune: Exploring the Efficacy of Pruning for Model Compression
Michael Zhu · Suyog Gupta
Workshop
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting Level 8 + 15 #15
On the Limitation of Local Intrinsic Dimensionality for Characterizing the Subspaces of Adversarial Examples
Pei-Hsuan Lu · Pin-Yu Chen · Chia-Mu Yu
Workshop
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting Level 8 + 15 #16
Hockey-Stick GAN
Edgar Minasyan · John Whaley
Workshop
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting Level 8 + 15 #17
Fast Node Embeddings: Learning Ego-Centric Representations
Tiago Pimentel · Adriano Veloso · Nivio Ziviani
Workshop
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting Level 8 + 15 #18
Synthesizing Audio with GANs
Chris Donahue · Julian McAuley · Miller Puckette
Workshop
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting Level 8 + 15 #19
Multi-Agent Generative Adversarial Imitation Learning
Jiaming Song · Hongyu Ren · Dorsa Sadigh · Stefano Ermon
Workshop
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting Level 8 + 15 #20
LEARNING AND ANALYZING VECTOR ENCODING OF SYMBOLIC REPRESENTATION
· · Paul Smolensky · Rishabh Singh
Workshop
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting Level 8 + 15 #21
SGD on Random Mixtures: Private Machine Learning under Data Breach Threats
Kangwook Lee · Kyungmin Lee · Hoon Kim · Changho Suh · Kannan Ramchandran
Workshop
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting Level 8 + 15 #22
Neuron as an Agent
Shohei Ohsawa · Kei Akuzawa · Tatsuya Matsushima · Gustavo Bezerra · Yusuke Iwasawa · Hiroshi Kajino · · Yutaka Matsuo
Workshop
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting Level 8 + 15 #23
Weightless: Lossy weight encoding for deep neural network compression
Brandon Reagen · Udit Gupta · Robert Adolf · Michael Mitzenmacher · Alexander Rush · Alexander Rush · Gu-Yeon Wei
Workshop
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting Level 8 + 15 #24
A Dataset To Evaluate The Representations Learned By Video Prediction Models
Ryan Szeto · Simon Stent · German Ros · Jason J Corso
Workshop
Tue May 1st 11:00 AM -- 01:00 PM @ East Meeting Level 8 + 15 #25
Empirical Analysis of the Hessian of Over-Parametrized Neural Networks
Levent Sagun · Utku Evci · Veli Ugur Guney · Yann Dauphin · Leon Bottou
Break
Tue May 1st 01:00 -- 02:30 PM @ On Your Own
Lunch
Invited Talk
Tue May 1st 02:30 -- 03:15 PM @ Exhibition Hall A
Visual Learning With Unlabeled Video and Look-Around Policies
Kristen Grauman
Oral
Tue May 1st 03:15 -- 03:30 PM @ Exhibition Hall A
Boosting Dilated Convolutional Networks with Mixed Tensor Decompositions
Nadav Cohen · Ronen Tamari · Amnon Shashua
Oral
Tue May 1st 03:30 -- 03:45 PM @ Exhibition Hall A
Spherical CNNs
Taco Cohen · Mario Geiger · Jonas Koehler · Max Welling
Oral
Tue May 1st 03:45 -- 04:00 PM @ Exhibition Hall A
Zero-Shot Visual Imitation
Deepak Pathak · Parsa Mahmoudieh · Guanghao Luo · Pulkit Agrawal · Dian Chen · Fred Shentu · Evan Shelhamer · Jitendra Malik · Alexei Efros · Trevor Darrell
Oral
Tue May 1st 04:00 -- 04:15 PM @ Exhibition Hall A
Multi-Scale Dense Networks for Resource Efficient Image Classification
Gao Huang · Danlu Chen · Tianhong Li · Felix Wu · Laurens van der Maaten · Kilian Q Weinberger
Break
Tue May 1st 04:15 -- 04:30 PM @ Ballroom ABC
Coffee Break
Poster
Tue May 1st 04:30 -- 06:30 PM @ East Meeting level; 1,2,3 #1
FearNet: Brain-Inspired Model for Incremental Learning
Ronald Kemker · Christopher Kanan
Poster
Tue May 1st 04:30 -- 06:30 PM @ East Meeting level; 1,2,3 #2
Variational Inference of Disentangled Latent Concepts from Unlabeled Observations
Abhishek Kumar · Prasanna Sattigeri · Avinash Balakrishnan
Poster
Tue May 1st 04:30 -- 06:30 PM @ East Meeting level; 1,2,3 #3
Meta-Learning for Semi-Supervised Few-Shot Classification
Mengye Ren · Eleni Triantafillou · Sachin Ravi · Jake Snell · Kevin Swersky · Joshua B Tenenbaum · Hugo Larochelle · Richard Zemel
Poster
Tue May 1st 04:30 -- 06:30 PM @ East Meeting level; 1,2,3 #4
Neural Sketch Learning for Conditional Program Generation
Vijayaraghavan Murali · Letao Qi · Swarat Chaudhuri · Chris Jermaine
Poster
Tue May 1st 04:30 -- 06:30 PM @ East Meeting level; 1,2,3 #5
Deep Neural Networks as Gaussian Processes
Jaehoon Lee · Yasaman Bahri · Roman Novak · Samuel S Schoenholz · Jeffrey Pennington · Jascha Sohl-Dickstein
Poster
Tue May 1st 04:30 -- 06:30 PM @ East Meeting level; 1,2,3 #6
Initialization matters: Orthogonal Predictive State Recurrent Neural Networks
Krzysztof Choromanski · Carlton Downey · Byron Boots
Poster
Tue May 1st 04:30 -- 06:30 PM @ East Meeting level; 1,2,3 #7
Expressive power of recurrent neural networks
Valentin Khrulkov · Alexander Novikov · Ivan Oseledets
Poster
Tue May 1st 04:30 -- 06:30 PM @ East Meeting level; 1,2,3 #8
Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models
Pouya Samangouei · Maya Kabkab · Rama Chellappa
Poster
Tue May 1st 04:30 -- 06:30 PM @ East Meeting level; 1,2,3 #9
Variance Reduction for Policy Gradient with Action-Dependent Factorized Baselines
Cathy Wu · Aravind Rajeswaran · Yan Duan · Vikash Kumar · Alexandre M Bayen · Sham M Kakade · Igor Mordatch · Pieter Abbeel
Poster
Tue May 1st 04:30 -- 06:30 PM @ East Meeting level; 1,2,3 #10
Certified Defenses against Adversarial Examples
Aditi Raghunathan · Jacob Steinhardt · Percy Liang
Poster
Tue May 1st 04:30 -- 06:30 PM @ East Meeting level; 1,2,3 #11
Semantic Interpolation in Implicit Models
Yannic Kilcher · Aurelien Lucchi · Thomas Hofmann
Poster
Tue May 1st 04:30 -- 06:30 PM @ East Meeting level; 1,2,3 #12
Leave no Trace: Learning to Reset for Safe and Autonomous Reinforcement Learning
Benjamin Eysenbach · Shixiang Gu · Julian Ibarz · Sergey Levine
Poster
Tue May 1st 04:30 -- 06:30 PM @ East Meeting level; 1,2,3 #13
Learning One-hidden-layer Neural Networks with Landscape Design
Rong Ge · Jason Lee · Tengyu Ma
Poster
Tue May 1st 04:30 -- 06:30 PM @ East Meeting level; 1,2,3 #14
Thermometer Encoding: One Hot Way To Resist Adversarial Examples
Jacob Buckman · Aurko Roy · Colin Raffel · Ian Goodfellow
Poster
Tue May 1st 04:30 -- 06:30 PM @ East Meeting level; 1,2,3 #15
Training GANs with Optimism
Constantinos C Daskalakis · Andrew Ilyas · Vasilis Syrgkanis · Haoyang Zeng
Poster
Tue May 1st 04:30 -- 06:30 PM @ East Meeting level; 1,2,3 #16
Hierarchical and Interpretable Skill Acquisition in Multi-task Reinforcement Learning
Tianmin Shu · Caiming Xiong · richard socher
Poster
Tue May 1st 04:30 -- 06:30 PM @ East Meeting level; 1,2,3 #17
The Reactor: A fast and sample-efficient Actor-Critic agent for Reinforcement Learning
Audrunas Gruslys · Will Dabney · Mohammad Gheshlaghi Azar · Bilal Piot · Marc G Bellemare · Remi Munos
Poster
Tue May 1st 04:30 -- 06:30 PM @ East Meeting level; 1,2,3 #18
Distributed Prioritized Experience Replay
Daniel Horgan · John Quan · David Budden · Gabriel Barth-maron · Matteo Hessel · Hado van Hasselt · David Silver
Poster
Tue May 1st 04:30 -- 06:30 PM @ East Meeting level; 1,2,3 #19
Adversarial Dropout Regularization
Kuniaki Saito · Yoshitaka Ushiku · Tatsuya Harada · Kate Saenko
Poster
Tue May 1st 04:30 -- 06:30 PM @ East Meeting level; 1,2,3 #20
Countering Adversarial Images using Input Transformations
Chuan Guo · Mayank Rana · Moustapha Cisse · Laurens van der Maaten
Poster
Tue May 1st 04:30 -- 06:30 PM @ East Meeting level; 1,2,3 #21
Generating Natural Adversarial Examples
Zhengli Zhao · Dheeru Dua · Sameer Singh
Poster
Tue May 1st 04:30 -- 06:30 PM @ East Meeting level; 1,2,3 #22
Spherical CNNs
Taco Cohen · Mario Geiger · Jonas Koehler · Max Welling
Poster
Tue May 1st 04:30 -- 06:30 PM @ East Meeting level; 1,2,3 #23
Intrinsic Motivation and Automatic Curricula via Asymmetric Self-Play
Sainbayar Sukhbaatar · Zeming Lin · Ilya Kostrikov · Gabriel Synnaeve · Arthur Szlam · Rob Fergus
Poster
Tue May 1st 04:30 -- 06:30 PM @ East Meeting level; 1,2,3 #24
Beyond Word Importance: Contextual Decomposition to Extract Interactions from LSTMs
William Murdoch · Peter J Liu · Bin Yu
Poster
Tue May 1st 04:30 -- 06:30 PM @ East Meeting level; 1,2,3 #25
Unsupervised Neural Machine Translation
Mikel Artetxe · Gorka Labaka · Eneko Agirre · Kyunghyun Cho
Poster
Tue May 1st 04:30 -- 06:30 PM @ East Meeting level; 1,2,3 #26
Smooth Loss Functions for Deep Top-k Classification
Leonard Berrada · Andrew Zisserman · M. Pawan Kumar
Poster
Tue May 1st 04:30 -- 06:30 PM @ East Meeting level; 1,2,3 #27
Synthetic and Natural Noise Both Break Neural Machine Translation
Yonatan Belinkov · Yonatan Bisk
Poster
Tue May 1st 04:30 -- 06:30 PM @ East Meeting level; 1,2,3 #28
Can Neural Networks Understand Logical Entailment?
Richard Evans · David Saxton · David Amos · Pushmeet Kohli · Edward Grefenstette
Poster
Tue May 1st 04:30 -- 06:30 PM @ East Meeting level; 1,2,3 #29
Mastering the Dungeon: Grounded Language Learning by Mechanical Turker Descent
Zhilin Yang · Saizheng Zhang · Jack Urbanek · Will Feng · Alexander Miller · Arthur Szlam · Douwe Kiela · Jason Weston
Poster
Tue May 1st 04:30 -- 06:30 PM @ East Meeting level; 1,2,3 #30
Many Paths to Equilibrium: GANs Do Not Need to Decrease a Divergence At Every Step
William Fedus · Mihaela Rosca · Balaji Lakshminarayanan · Andrew Dai · Shakir Mohamed · Ian Goodfellow
Poster
Tue May 1st 04:30 -- 06:30 PM @ East Meeting level; 1,2,3 #31
Learning Latent Permutations with Gumbel-Sinkhorn Networks
gonzalo mena · David Belanger · Scott Linderman · Jasper Snoek
Poster
Tue May 1st 04:30 -- 06:30 PM @ East Meeting level; 1,2,3 #32
Can recurrent neural networks warp time?
Corentin Tallec · Yann Ollivier
Poster
Tue May 1st 04:30 -- 06:30 PM @ East Meeting level; 1,2,3 #34
Learning Differentially Private Recurrent Language Models
H. Brendan McMahan · Daniel Ramage · Kunal Talwar · Li Zhang
Poster
Tue May 1st 04:30 -- 06:30 PM @ East Meeting level; 1,2,3 #35
Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via Ranking
Aleksandar Bojchevski · Stephan Günnemann
Poster
Tue May 1st 04:30 -- 06:30 PM @ East Meeting level; 1,2,3 #36
SEARNN: Training RNNs with global-local losses
Rémi Leblond · Jean-Baptiste Alayrac · Anton Osokin · Simon Lacoste-Julien
Poster
Tue May 1st 04:30 -- 06:30 PM @ East Meeting level; 1,2,3 #37
Learning to Teach
Yang Fan · Fei Tian · Tao Qin · Tie-Yan Liu
Poster
Tue May 1st 04:30 -- 06:30 PM @ East Meeting level; 1,2,3 #38
Active Learning for Convolutional Neural Networks: A Core-Set Approach
Ozan Sener · Silvio Savarese
Poster
Tue May 1st 04:30 -- 06:30 PM @ East Meeting level; 1,2,3 #39
Sparse Persistent RNNs: Squeezing Large Recurrent Networks On-Chip
Feiwen Zhu · Jeff Pool · Michael Andersch · Jeremy Appleyard · Fung Xie
Poster
Tue May 1st 04:30 -- 06:30 PM @ East Meeting level; 1,2,3 #40
WRPN: Wide Reduced-Precision Networks
Asit Mishra · Eriko Nurvitadhi · Jeffrey J Cook · Debbie Marr
Poster
Tue May 1st 04:30 -- 06:30 PM @ East Meeting level; 1,2,3 #41
Deep Voice 3: Scaling Text-to-Speech with Convolutional Sequence Learning
Wei Ping · Kainan Peng · Andrew Gibiansky · Sercan Arik · Ajay Kannan · SHARAN NARANG · Jonathan Raiman · John Miller
Poster
Tue May 1st 04:30 -- 06:30 PM @ East Meeting level; 1,2,3 #42
Spectral Normalization for Generative Adversarial Networks
Takeru Miyato · Toshiki Kataoka · Masanori Koyama · Yuichi Yoshida
Workshop
Tue May 1st 04:30 -- 06:30 PM @ East Meeting Level 8 + 15 #1
Universal Successor Representations for Transfer Reinforcement Learning
Chen Ma · Junfeng Wen ·
Workshop
Tue May 1st 04:30 -- 06:30 PM @ East Meeting Level 8 + 15 #2
A Proximal Block Coordinate Descent Algorithm for Deep Neural Network Training
Tsz Kit Lau · Jinshan Zeng · Baoyuan Wu · Yuan Yao
Workshop
Tue May 1st 04:30 -- 06:30 PM @ East Meeting Level 8 + 15 #3
Jointly Learning "What" and "How" from Instructions and Goal-States
Dzmitry Bahdanau · Felix Hill · Jan Leike · Edward Hughes · Pushmeet Kohli · Edward Grefenstette
Workshop
Tue May 1st 04:30 -- 06:30 PM @ East Meeting Level 8 + 15 #4
Deep learning mutation prediction enables early stage lung cancer detection in liquid biopsy
Steven T. Kothen-Hill · Asaf Zviran · Rafael Schulman · Sunil Deochand · Federico Gaiti · Dillon Maloney · Kevin Huang · Willey Liao · Nicolas Robine · Nathaniel Omans · Dan Landau
Workshop
Tue May 1st 04:30 -- 06:30 PM @ East Meeting Level 8 + 15 #5
Evaluating visual "common sense" using fine-grained classification and captioning tasks
Raghav Goyal · Farzaneh Mahdisoltani · Guillaume Berger · Waseem Gharbieh · Ingo Bax · Roland Memisevic
Workshop
Tue May 1st 04:30 -- 06:30 PM @ East Meeting Level 8 + 15 #6
Deep Neural Maps
Mehran Pesteie · Purang Abolmaesumi · Robert Rohling
Workshop
Tue May 1st 04:30 -- 06:30 PM @ East Meeting Level 8 + 15 #7
Comparing Fixed and Adaptive Computation Time for Recurrent Neural Networks
Daniel Fojo · Víctor Campos · Xavier Giro-i-Nieto
Workshop
Tue May 1st 04:30 -- 06:30 PM @ East Meeting Level 8 + 15 #8
Compression by the signs: distributed learning is a two-way street
Jeremy Bernstein · Yu-Xiang Wang · Kamyar Azizzadenesheli · anima anandkumar
Workshop
Tue May 1st 04:30 -- 06:30 PM @ East Meeting Level 8 + 15 #9
Rethinking Style and Content Disentanglement in Variational Autoencoders
Rui Shu · Shengjia Zhao · Mykel J Kochenderfer
Workshop
Tue May 1st 04:30 -- 06:30 PM @ East Meeting Level 8 + 15 #10
Clustering Meets Implicit Generative Models
Francesco Locatello · Damien Vincent · Ilya Tolstikhin · Gunnar Rätsch · · Bernhard Schoelkopf
Workshop
Tue May 1st 04:30 -- 06:30 PM @ East Meeting Level 8 + 15 #11
Minimally Redundant Laplacian Eigenmaps
David Pfau · Christopher P Burgess
Workshop
Tue May 1st 04:30 -- 06:30 PM @ East Meeting Level 8 + 15 #12
Neural Program Search: Solving Programming Tasks from Description and Examples
Illia Polosukhin ·
Workshop
Tue May 1st 04:30 -- 06:30 PM @ East Meeting Level 8 + 15 #13
ReinforceWalk: Learning to Walk in Graph with Monte Carlo Tree Search
· Jianshu Chen · Po-Sen Huang · Yuqing Guo · Jianfeng Gao
Workshop
Tue May 1st 04:30 -- 06:30 PM @ East Meeting Level 8 + 15 #14
Adversarial Spheres
Justin Gilmer · Luke Metz · Fartash Faghri · Samuel S Schoenholz · · Martin Wattenberg · Ian Goodfellow
Workshop
Tue May 1st 04:30 -- 06:30 PM @ East Meeting Level 8 + 15 #15
Attacking the Madry Defense Model with $L_1$-based Adversarial Examples
Yash Sharma · Pin-Yu Chen
Workshop
Tue May 1st 04:30 -- 06:30 PM @ East Meeting Level 8 + 15 #16
Stable Distribution Alignment Using the Dual of the Adversarial Distance
Ben Usman · Kate Saenko · Brian Kulis
Workshop
Tue May 1st 04:30 -- 06:30 PM @ East Meeting Level 8 + 15 #17
A Flexible Approach to Automated RNN Architecture Generation
Martin Schrimpf · Stephen Merity · James Bradbury · richard socher
Workshop
Tue May 1st 04:30 -- 06:30 PM @ East Meeting Level 8 + 15 #18
Variance-based Gradient Compression for Efficient Distributed Deep Learning
Yusuke Tsuzuku · Hiroto Imachi · Takuya Akiba
Workshop
Tue May 1st 04:30 -- 06:30 PM @ East Meeting Level 8 + 15 #19
A differentiable BLEU loss. Analysis and first results
noe casas · Marta R. Costa-jussà · Jose A.R Fonollosa
Workshop
Tue May 1st 04:30 -- 06:30 PM @ East Meeting Level 8 + 15 #20
Kronecker Recurrent Units
Cijo Jose · Moustapha Cisse · Francois Fleuret
Workshop
Tue May 1st 04:30 -- 06:30 PM @ East Meeting Level 8 + 15 #21
Expert-based reward function training: the novel method to train sequence generators
Joji Toyama · Yusuke Iwasawa · Kotaro Nakayama · Yutaka Matsuo
Workshop
Tue May 1st 04:30 -- 06:30 PM @ East Meeting Level 8 + 15 #22
The loss surface and expressivity of deep convolutional neural networks
Quynh Nguyen · Matthias Hein
Workshop
Tue May 1st 04:30 -- 06:30 PM @ East Meeting Level 8 + 15 #23
Semi-Supervised Few-Shot Learning with MAML
Rinu Boney · Alexander Ilin
Workshop
Tue May 1st 04:30 -- 06:30 PM @ East Meeting Level 8 + 15 #24
Stacked Filters Stationary Flow For Hardware-Oriented Acceleration Of Deep Convolutional Neural Networks
Yuechao Gao · Nianhong Liu · Zhang Sheng