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Break
Mon May 6th 07:00 AM -- 06:30 PM @ None
Registration Desk Open
Break
Mon May 6th 08:45 -- 09:00 AM @ Great Hall AD
Opening Remarks
Invited Talk
Mon May 6th 09:00 -- 09:45 AM @ Great Hall AD
Highlights of Recent Developments in Algorithmic Fairness
Cynthia Dwork
Oral
Mon May 6th 09:45 -- 10:00 AM @ Great Hall AD
Generating High Fidelity Images with Subscale Pixel Networks and Multidimensional Upscaling
Jacob Menick · Nal Kalchbrenner
Workshop
Mon May 6th 09:45 AM -- 06:30 PM @ Room R01
The 2nd Learning from Limited Labeled Data (LLD) Workshop: Representation Learning for Weak Supervision and Beyond
Isabelle Augenstein · Stephen Bach · Matthew Blaschko · Eugene Belilovsky · Edouard Oyallon · Anthony Platanios · Alex Ratner · Christopher Re · Xiang Ren · Paroma Varma
Workshop
Mon May 6th 09:45 AM -- 01:00 PM @ Room R02
Deep Reinforcement Learning Meets Structured Prediction
Chen Liang · Ni Lao · Wang Ling · Zita Marinho · Yuandong Tian · Lu Wang · Jason D Williams · Audrey Durand · Andre Martins
Workshop
Mon May 6th 09:45 AM -- 06:30 PM @ Room R03
Debugging Machine Learning Models
Julius Adebayo · Himabindu Lakkaraju · Sarah Tan · Rich Caruana · D. Sculley · Jacob Steinhardt
Workshop
Mon May 6th 09:45 AM -- 06:30 PM @ Room R04
Structure & Priors in Reinforcement Learning (SPiRL)
Pierre-Luc Bacon · Marc Deisenroth · Chelsea Finn · Erin Grant · Thomas L Griffiths · Abhishek Gupta · Nicolas Heess · Michael L. Littman · Junhyuk Oh
Workshop
Mon May 6th 09:45 AM -- 06:30 PM @ Room R05
AI for Social Good
Margaux Luck · Myriam Cote · Kris Sankaran · Sean McGregor · Jonnie Penn · Virgile Sylvain · Tristan Sylvain · Geneviève Boucher · Rayid Ghani · Yoshua Bengio · Kentaro Toyama
Workshop
Mon May 6th 09:45 AM -- 06:30 PM @ Room R06
Safe Machine Learning: Specification, Robustness, and Assurance
Silvia Chiappa · Victoria Krakovna · Adrià Garriga-Alonso · Jonathan Uesato · Andrew Trask · Christina Heinze-Deml · Ray Jiang · Adrian Weller
Workshop
Mon May 6th 09:45 AM -- 06:30 PM @ Room R07
Representation Learning on Graphs and Manifolds
William Hamilton · Frederic Sala · Peter Battaglia · Joan Bruna · Thomas Kipf · Yujia Li · Razvan Pascanu · Adriana Romero · Petar Veličković · Marinka Zitnik · Maximilian Nickel · Beliz Gunel · Albert Gu · Christopher Re
Workshop
Mon May 6th 09:45 AM -- 06:30 PM @ Room R08
Reproducibility in Machine Learning
Nan Rosemary Ke · Alex Lamb · OLEXA Ivan BILANIUK · Anirudh Goyal Alias Parth Goyal · Aaron Courville · Yoshua Bengio
Workshop
Mon May 6th 09:45 AM -- 06:30 PM @ Room R09
Task-Agnostic Reinforcement Learning (TARL)
Danijar Hafner · Deepak Pathak · Frederik Ebert · Marc G Bellemare · Raia Hadsell · Rowan McAllister · Amy Zhang · Joelle Pineau · Ahmed Touati · Roberto Calandra
Oral
Mon May 6th 10:00 -- 10:15 AM @ Great Hall AD
BA-Net: Dense Bundle Adjustment Networks
Chengzhou Tang · Ping Tan
Oral
Mon May 6th 10:15 -- 10:30 AM @ Great Hall AD
Large Scale GAN Training for High Fidelity Natural Image Synthesis
Andrew Brock · Jeff Donahue · Karen Simonyan
Break
Mon May 6th 10:30 -- 11:00 AM @ Hall B-1
Coffee Break
Break
Mon May 6th 01:00 -- 02:30 PM @ on your own
Lunch - on your own
Invited Talk
Mon May 6th 02:30 -- 03:15 PM @ Great Hall AD
Learning Representations Using Causal Invariance
Leon Bottou
Oral
Mon May 6th 03:15 -- 03:30 PM @ Great Hall AD
On Random Deep Weight-Tied Autoencoders: Exact Asymptotic Analysis, Phase Transitions, and Implications to Training
Ping Li · Phan-Minh Nguyen
Workshop
Mon May 6th 03:15 -- 06:30 PM @ Room R02
Deep Generative Models for Highly Structured Data
Adji Bousso Dieng · Yoon Kim · Siva Reddy · Kyunghyun Cho · Chris Dyer · David Blei · Phil Blunsom
Oral
Mon May 6th 03:30 -- 03:45 PM @ Great Hall AD
How Powerful are Graph Neural Networks?
Keyulu Xu · Weihua Hu · Jure Leskovec · Stefanie Jegelka
Oral
Mon May 6th 03:45 -- 04:00 PM @ Great Hall AD
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks
Jonathan Frankle · Michael Carbin
Break
Mon May 6th 04:00 -- 04:30 PM @ Hall B-1
Coffee Break
Break
Mon May 6th 06:30 -- 07:30 PM @ Great Hall Pre-Function, Hall B-1
Opening Reception
Break
Mon May 6th 07:00 -- 07:30 PM @ Rivergate Room
Newcomers Reception
Break
Tue May 7th 08:00 AM -- 06:30 PM @ None
Registration Desk Open
Invited Talk
Tue May 7th 09:00 -- 09:45 AM @ Great Hall AD
Can Machine Learning Help to Conduct a Planetary Healthcheck?
Emily Shuckburgh
Workshop
Tue May 7th 09:00 AM -- 06:30 PM @ Room R01
LatinX in AI and Black in AI Joint Workshop
Oral
Tue May 7th 09:45 -- 10:00 AM @ Great Hall AD
Learning Protein Structure with a Differentiable Simulator
John Ingraham · Adam J Riesselman · Chris Sander · Debora Marks
Oral
Tue May 7th 10:00 -- 10:15 AM @ Great Hall AD
Enabling Factorized Piano Music Modeling and Generation with the MAESTRO Dataset
Curtis Hawthorne · Andriy Stasyuk · Adam Roberts · Ian Simon · Anna Huang · Sander Dieleman · Erich K Elsen · Jesse Engel · Douglas Eck
Oral
Tue May 7th 10:15 -- 10:30 AM @ Great Hall AD
A Unified Theory of Early Visual Representations from Retina to Cortex through Anatomically Constrained Deep CNNs
Jack Lindsey · Samuel Ocko · Surya Ganguli · Stephane Deny
Break
Tue May 7th 10:30 -- 11:00 AM @ Hall B-1
Coffee Break
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #1
Random mesh projectors for inverse problems
Konik Kothari · Sidharth Gupta · Maarten V de Hoop · Ivan Dokmanic
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #2
Improving MMD-GAN Training with Repulsive Loss Function
Wei Wang · Yuan Sun · Saman Halgamuge
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #3
STCN: Stochastic Temporal Convolutional Networks
Emre Aksan · Otmar Hilliges
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #4
GENERATING HIGH FIDELITY IMAGES WITH SUBSCALE PIXEL NETWORKS AND MULTIDIMENSIONAL UPSCALING
Jacob Menick · Nal Kalchbrenner
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #5
Diversity and Depth in Per-Example Routing Models
Prajit Ramachandran · Quoc V Le
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #6
GANSynth: Adversarial Neural Audio Synthesis
Jesse Engel · Kumar Agrawal · Shuo Chen · Ishaan Gulrajani · Chris Donahue · Adam Roberts
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #7
Value Propagation Networks
Nantas Nardelli · Gabriel Synnaeve · Zeming Lin · Pushmeet Kohli · Philip Torr · Nicolas Usunier
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #8
Visual Reasoning by Progressive Module Networks
Seung Wook Kim · Makarand Tapaswi · Sanja Fidler
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #9
Overcoming the Disentanglement vs Reconstruction Trade-off via Jacobian Supervision
José Lezama
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #10
Minimal Images in Deep Neural Networks: Fragile Object Recognition in Natural Images
Sanjana Srivastava · Guy Ben-Yosef · Xavier Boix
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #11
Time-Agnostic Prediction: Predicting Predictable Video Frames
Dinesh Jayaraman · Frederik Ebert · Alexei Efros · Sergey Levine
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #12
Harmonizing Maximum Likelihood with GANs for Multimodal Conditional Generation
Soochan Lee · Junsoo Ha · Gunhee Kim
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #13
A Unified Theory of Early Visual Representations from Retina to Cortex through Anatomically Constrained Deep CNNs
Jack Lindsey · Samuel Ocko · Surya Ganguli · Stephane Deny
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #14
Human-level Protein Localization with Convolutional Neural Networks
Elisabeth Rumetshofer · Markus Hofmarcher · Clemens Röhrl · Sepp Hochreiter · Günter Klambauer
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #15
Model-Predictive Policy Learning with Uncertainty Regularization for Driving in Dense Traffic
Mikael Henaff · Alfredo Canziani · Yann LeCun
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #16
Bayesian Deep Convolutional Networks with Many Channels are Gaussian Processes
Roman Novak · Lechao Xiao · Yasaman Bahri · Jaehoon Lee · Greg Yang · Jiri Hron · Daniel Abolafia · Jeffrey Pennington · Jascha Sohl-Dickstein
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #17
Differentiable Learning-to-Normalize via Switchable Normalization
Ping Luo · jiamin ren · zhanglin peng · Ruimao Zhang · Jingyu Li
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #18
Learning a SAT Solver from Single-Bit Supervision
Daniel Selsam · Matthew Lamm · Benedikt B\"{u}nz · Percy Liang · Leonardo Moura · David L Dill
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #19
Big-Little Net: An Efficient Multi-Scale Feature Representation for Visual and Speech Recognition
Chun-Fu (Richard) Chen · Quanfu Fan · Neil Mallinar · Tom Sercu · Rogerio Feris
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #20
Unsupervised Discovery of Parts, Structure, and Dynamics
Zhenjia Xu · Zhijian Liu · Chen Sun · Kevin Murphy · William Freeman · Joshua B Tenenbaum · Jiajun Wu
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #21
ROBUST ESTIMATION VIA GENERATIVE ADVERSARIAL NETWORKS
Chao Gao · Jiyi Liu · Yuan Yao · Weizhi ZHU
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #22
Unsupervised Adversarial Image Reconstruction
Arthur Pajot · Emmanuel de Bézenac · patrick Gallinari
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #23
Explaining Image Classifiers by Counterfactual Generation
Chun-Hao Chang · Elliot Creager · Anna Goldenberg · David Duvenaud
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #24
Equi-normalization of Neural Networks
Pierre Stock · Benjamin Graham · Rémi Gribonval · Hervé Jégou
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #25
Biologically-Plausible Learning Algorithms Can Scale to Large Datasets
Wu Xiao · HONGLIN CHEN · Qianli Liao · Tomaso Poggio
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #26
ADef: an Iterative Algorithm to Construct Adversarial Deformations
Rima Alaifari · Giovanni S Alberti · Tandri Gauksson
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #27
Adversarial Domain Adaptation for Stable Brain-Machine Interfaces
Ali Farshchian · Juan Álvaro Gallego · Joseph Paul Cohen · Yoshua Bengio · Lee E Miller · Sara A Solla
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #28
Meta-Learning with Latent Embedding Optimization
Andrei Rusu · Dushyant Rao · Jakub Sygnowski · Oriol Vinyals · Razvan Pascanu · Simon Osindero · Raia Hadsell
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #29
Diversity-Sensitive Conditional Generative Adversarial Networks
Dingdong Yang · Seunghoon Hong · Yunseok Jang · Tianchen Zhao · Honglak Lee
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #30
LanczosNet: Multi-Scale Deep Graph Convolutional Networks
Renjie Liao · Zhizhen Zhao · Raquel Urtasun · Richard Zemel
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #31
Convolutional Neural Networks on Non-uniform Geometrical Signals Using Euclidean Spectral Transformation
Chiyu Jiang · Dequan Wang · Jingwei Huang · Philip Marcus · Matthias Niessner
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #32
Generating Multiple Objects at Spatially Distinct Locations
Tobias Hinz · Stefan Heinrich · Stefan Wermter
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #33
Disjoint Mapping Network for Cross-modal Matching of Voices and Faces
Yandong Wen · Mahmoud Al Ismail · Weiyang Liu · Bhiksha Raj · Rita Singh
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #34
A rotation-equivariant convolutional neural network model of primary visual cortex
Alexander Ecker · Fabian H Sinz · Emmanouil Froudarakis · Paul Fahey · Santiago A Cadena · Edgar Walker · Erick M Cobos · Jacob Reimer · Andreas Tolias · Matthias Bethge
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #35
Non-vacuous Generalization Bounds at the ImageNet Scale: a PAC-Bayesian Compression Approach
Wenda Zhou · Victor Veitch · Morgane Austern · Ryan P Adams · Peter Orbanz
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #36
Large Scale GAN Training for High Fidelity Natural Image Synthesis
Andrew Brock · Jeff Donahue · Karen Simonyan
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #37
Deep Convolutional Networks as shallow Gaussian Processes
Adrià Garriga-Alonso · Carl Edward Rasmussen · Laurence Aitchison
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #38
LeMoNADe: Learned Motif and Neuronal Assembly Detection in calcium imaging videos
Elke Kirschbaum · Manuel Haussmann · Steffen Wolf · Hannah Sonntag · Justus Schneider · Shehabeldin Elzoheiry · Oliver Kann · Daniel Durstewitz · Fred A Hamprecht
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #39
Learning Protein Structure with a Differentiable Simulator
John Ingraham · Adam J Riesselman · Chris Sander · Debora Marks
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #40
Latent Convolutional Models
ShahRukh Athar · Evgeny Burnaev · Victor Lempitsky
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #41
Visual Explanation by Interpretation: Improving Visual Feedback Capabilities of Deep Neural Networks
José Antonio Oramas Mogrovejo · Kaili Wang · Tinne Tuytelaars
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #42
Diffusion Scattering Transforms on Graphs
Fernando Gama · Alejandro Ribeiro · Joan Bruna
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #43
Spherical CNNs on Unstructured Grids
Chiyu Jiang · Jingwei Huang · Karthik Kashinath · Mr Prabhat · Philip Marcus · Matthias Niessner
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #44
Learning To Simulate
Nataniel Ruiz · Samuel Schulter · Manmohan Chandraker
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #45
The Singular Values of Convolutional Layers
Hanie Sedghi · Vineet Gupta · Phil Long
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #46
On the Minimal Supervision for Training Any Binary Classifier from Only Unlabeled Data
Nan Lu · Gang Niu · Aditya Krishna Menon · Masashi Sugiyama
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #47
Generating Multi-Agent Trajectories using Programmatic Weak Supervision
Eric Zhan · Stephan Zheng · Yisong Yue · Long Sha · Patrick Lucey
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #48
Learning Localized Generative Models for 3D Point Clouds via Graph Convolution
Diego Valsesia · Giulia Fracastoro · Enrico Magli
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #49
Approximating CNNs with Bag-of-local-Features models works surprisingly well on ImageNet
Wieland Brendel · Matthias Bethge
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #50
Mode Normalization
Lucas Deecke · Iain Murray · Hakan Bilen
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #51
Enabling Factorized Piano Music Modeling and Generation with the MAESTRO Dataset
Curtis Hawthorne · Andriy Stasyuk · Adam Roberts · Ian Simon · Anna Huang · Sander Dieleman · Erich K Elsen · Jesse Engel · Douglas Eck
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #52
Neural network gradient-based learning of black-box function interfaces
Alon Jacovi · guy hadash · Einat Kermany · Boaz Carmeli · Ofer Lavi · George M. Kour · Jonathan Berant
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #53
BA-Net: Dense Bundle Adjustment Networks
Chengzhou Tang · Ping Tan
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #54
K for the Price of 1: Parameter-efficient Multi-task and Transfer Learning
Pramod Kaushik Mudrakarta · Mark Sandler · Andrey Zhmoginov · Andrew Howard
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #55
Residual Non-local Attention Networks for Image Restoration
Yulun Zhang · Kunpeng Li · Kai Li · Bineng Zhong · Yun Fu
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #56
Eidetic 3D LSTM: A Model for Video Prediction and Beyond
Yunbo Wang · Lu Jiang · Ming-Hsuan Yang · Li-Jia Li · Mingsheng Long · Li Fei-Fei
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #57
Self-Monitoring Navigation Agent via Auxiliary Progress Estimation
Chih-Yao Ma · jiasen lu · Zuxuan Wu · Ghassan AlRegib · Zsolt Kira · richard socher · Caiming Xiong
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #58
ProbGAN: Towards Probabilistic GAN with Theoretical Guarantees
Hao He · Hao Wang · Guang-He Lee · Yonglong Tian
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #59
DELTA: DEEP LEARNING TRANSFER USING FEATURE MAP WITH ATTENTION FOR CONVOLUTIONAL NETWORKS
Xingjian Li · Haoyi Xiong · Hanchao Wang · Yuxuan Rao · Liping Liu · Luke Huan
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #60
A Data-Driven and Distributed Approach to Sparse Signal Representation and Recovery
Ali Mousavi · Gautam Dasarathy · Richard Baraniuk
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #61
Context-adaptive Entropy Model for End-to-end Optimized Image Compression
Jooyoung Lee · Seunghyun Cho · Seung-Kwon Beack
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #62
StrokeNet: A Neural Painting Environment
Ningyuan Zheng · Yf Jiang · Dingjiang Huang
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #63
Dynamic Channel Pruning: Feature Boosting and Suppression
Xitong Gao · Yiren Zhao · Łukasz Dudziak · Robert Mullins · Cheng-zhong Xu
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #64
Learning to Infer and Execute 3D Shape Programs
Yonglong Tian · Andrew Luo · Xingyuan Sun · Kevin Ellis · William Freeman · Joshua B Tenenbaum · Jiajun Wu
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #65
Emerging Disentanglement in Auto-Encoder Based Unsupervised Image Content Transfer
Ori Press · Tomer Galanti · Sagie Benaim · Lior Wolf
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #66
Deep Decoder: Concise Image Representations from Untrained Non-convolutional Networks
Reinhard Heckel · Paul Hand
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #67
AD-VAT: An Asymmetric Dueling mechanism for learning Visual Active Tracking
Fangwei Zhong · peng sun · Wenhan Luo · Tingyun Yan · Yizhou Wang
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #68
Visual Semantic Navigation using Scene Priors
Wei Yang · Xiaolong Wang · Ali Farhadi · Abhinav Gupta · Roozbeh Mottaghi
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #69
Deep Learning 3D Shapes Using Alt-az Anisotropic 2-Sphere Convolution
Min Liu · Fupin Yao · Chiho Choi · Ayan Sinha · Karthik Ramani
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #70
DPSNet: End-to-end Deep Plane Sweep Stereo
Sunghoon Im · Hae-Gon Jeon · Stephen Lin · In Kweon
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #71
Learning what you can do before doing anything
Oleh Rybkin · Karl Pertsch · Kosta Derpanis · Kostas Daniilidis · Andrew Jaegle
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #72
Learning to Describe Scenes with Programs
Yunchao Liu · Zheng Wu · Daniel Ritchie · William Freeman · Joshua B Tenenbaum · Jiajun Wu
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #73
GAN Dissection: Visualizing and Understanding Generative Adversarial Networks
David Bau · Jun-Yan Zhu · Hendrik Strobelt · Bolei Zhou · Joshua Tenenbaum · William Freeman · Antonio Torralba
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #74
Bounce and Learn: Modeling Scene Dynamics with Real-World Bounces
Senthil Purushwalkam · Abhinav Gupta · Danny Kaufman · Bryan Russell
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #75
RotDCF: Decomposition of Convolutional Filters for Rotation-Equivariant Deep Networks
Xiuyuan Cheng · Qiang Qiu · Robert Calderbank · Guillermo Sapiro
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #76
code2seq: Generating Sequences from Structured Representations of Code
Uri Alon · Shaked Brody · Omer Levy · Eran Yahav
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #77
Augmented Cyclic Adversarial Learning for Low Resource Domain Adaptation
Ehsan Hosseini-Asl · Yingbo Zhou · Caiming Xiong · richard socher
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #78
Learning Mixed-Curvature Representations in Product Spaces
Albert Gu · Frederic Sala · Beliz Gunel · Christopher Re
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #79
InstaGAN: Instance-aware Image-to-Image Translation
Sangwoo Mo · Minsu Cho · Jinwoo Shin
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #80
Multi-class classification without multi-class labels
Yen-Chang Hsu · Zhaoyang Lv · Joel Schlosser · Phillip Odom · Zsolt Kira
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #81
Bayesian Prediction of Future Street Scenes using Synthetic Likelihoods
Apratim Bhattacharyya · Mario Fritz · Bernt Schiele
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #82
Feature Intertwiner for Object Detection
Hongyang Li · Bo Dai · Shaoshuai Shi · Wanli Ouyang · Xiaogang Wang
Poster
Tue May 7th 11:00 AM -- 01:00 PM @ Great Hall BC #83
Recall Traces: Backtracking Models for Efficient Reinforcement Learning
Anirudh Goyal Alias Parth Goyal · Philemon Brakel · William Fedus · Soumye Singhal · Timothy Lillicrap · Sergey Levine · Hugo Larochelle · Yoshua Bengio
Break
Tue May 7th 01:00 -- 02:30 PM @ on your own
Lunch - on your own
Invited Talk
Tue May 7th 02:30 -- 03:15 PM @ Great Hall AD
Adversarial Machine Learning
Ian Goodfellow
Oral
Tue May 7th 03:15 -- 03:30 PM @ Great Hall AD
Slalom: Fast, Verifiable and Private Execution of Neural Networks in Trusted Hardware
Florian Tramer · Dan Boneh
Oral
Tue May 7th 03:30 -- 03:45 PM @ Great Hall AD
Learning to Remember More with Less Memorization
Hung T Le · Truyen Tran · Svetha Venkatesh
Oral
Tue May 7th 03:45 -- 04:00 PM @ Great Hall AD
Learning Robust Representations by Projecting Superficial Statistics Out
Haohan Wang · Zexue He · Zachary Lipton · Eric P Xing
Oral
Tue May 7th 04:00 -- 04:15 PM @ Great Hall AD
ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness
Robert Geirhos · Patricia Rubisch · Claudio Michaelis · Matthias Bethge · Felix Wichmann · Wieland Brendel
Break
Tue May 7th 04:15 -- 04:30 PM @ Hall B-1
Coffee Break
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #1
SNAS: stochastic neural architecture search
Sirui Xie · Hehui Zheng · Chunxiao Liu · Liang Lin
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #2
Predict then Propagate: Graph Neural Networks meet Personalized PageRank
Johannes Klicpera · Aleksandar Bojchevski · Stephan Günnemann
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #3
Improving Generalization and Stability of Generative Adversarial Networks
Hoang Thanh-Tung · Truyen Tran · Svetha Venkatesh
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #4
Beyond Pixel Norm-Balls: Parametric Adversaries using an Analytically Differentiable Renderer
Hsueh-Ti Derek Liu · Michael Tao · Chun-Liang Li · Derek Nowrouzezahrai · Alec Jacobson
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #5
L2-Nonexpansive Neural Networks
Haifeng Qian · Mark N Wegman
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #6
A Variational Inequality Perspective on Generative Adversarial Networks
Gauthier Gidel · Hugo Berard · Gaëtan Vignoud · Pascal Vincent · Simon Lacoste-Julien
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #7
PATE-GAN: Generating Synthetic Data with Differential Privacy Guarantees
James Jordon · Jinsung Yoon · Mihaela Schaar
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #8
Revealing interpretable object representations from human behavior
Charles Zheng · Francisco Pereira · Chris I Baker · Martin N Hebart
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #9
Robust Conditional Generative Adversarial Networks
Grigorios Chrysos · Jean Kossaifi · Stefanos Zafeiriou
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #10
Learning Robust Representations by Projecting Superficial Statistics Out
Haohan Wang · Zexue He · Zachary Lipton · Eric P Xing
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #11
Towards GAN Benchmarks Which Require Generalization
Ishaan Gulrajani · Colin Raffel · Luke Metz
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #12
Learning To Solve Circuit-SAT: An Unsupervised Differentiable Approach
Saeed Amizadeh · Sergiy Matusevych · Markus Weimer
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #13
Learnable Embedding Space for Efficient Neural Architecture Compression
Shengcao Cao · Xiaofang Wang · Kris M Kitani
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #14
Post Selection Inference with Incomplete Maximum Mean Discrepancy Estimator
Makoto Yamada · Yi Wu · Yao Hung Tsai · Hirofumi Ohta · Ruslan Salakhutdinov · Ichiro Takeuchi · Kenji Fukumizu
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #15
PeerNets: Exploiting Peer Wisdom Against Adversarial Attacks
Jan Svoboda · Jonathan Masci · Federico Monti · Michael Bronstein · Leonidas Guibas
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #16
CAMOU: Learning Physical Vehicle Camouflages to Adversarially Attack Detectors in the Wild
Yang Zhang · Hassan Foroosh · Phiip David · Boqing Gong
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #18
signSGD via Zeroth-Order Oracle
Sijia Liu · Pin-Yu Chen · Xiangyi Chen · Mingyi Hong
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #19
SOM-VAE: Interpretable Discrete Representation Learning on Time Series
Vincent Fortuin · Matthias Hüser · Francesco Locatello · Heiko Strathmann · Gunnar Rätsch
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #20
Generative Code Modeling with Graphs
Marc Brockschmidt · Miltiadis Allamanis · Alexander Gaunt · Oleksandr Polozov
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #21
Evaluating Robustness of Neural Networks with Mixed Integer Programming
Vincent Tjeng · Kai Xiao · Russ Tedrake
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #22
How Powerful are Graph Neural Networks?
Keyulu Xu · Weihua Hu · Jure Leskovec · Stefanie Jegelka
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #23
Graph Wavelet Neural Network
Bingbing Xu · Huawei Shen · Qi Cao · Yunqi Qiu · Xueqi Cheng
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #24
Whitening and Coloring Batch Transform for GANs
Aliaksandr Siarohin · Enver Sangineto · Nicu Sebe
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #25
Benchmarking Neural Network Robustness to Common Corruptions and Perturbations
Dan Hendrycks · Thomas Dietterich
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #26
Boosting Robustness Certification of Neural Networks
Gagandeep Singh · Timon Gehr · Markus Püschel · Martin Vechev
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #27
Conditional Network Embeddings
Bo Kang · Jefrey Lijffijt · Tijl De Bie
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #28
Multi-Domain Adversarial Learning
Alice Schoenauer Sebag · Louise E Heinrich · Marc Schoenauer · Michele Sebag · Lani Wu · Steven Altschuler
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #29
Learning to Remember More with Less Memorization
Hung T Le · Truyen Tran · Svetha Venkatesh
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #30
RelGAN: Relational Generative Adversarial Networks for Text Generation
Weili Nie · Nina Narodytska · Ankit B Patel
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #31
A Statistical Approach to Assessing Neural Network Robustness
Stefan Webb · Tom Rainforth · Yee Whye Teh · M. Pawan Kumar
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #32
Robustness May Be at Odds with Accuracy
Dimitris Tsipras · Shibani Santurkar · Logan Engstrom · Alexander Turner · Aleksander Madry
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #33
Verification of Non-Linear Specifications for Neural Networks
Chongli Qin · Krishnamurthy Dvijotham · Brendan ODonoghue · Rudy R Bunel · Robert W Stanforth · Sven Gowal · Jonathan Uesato · Grzegorz Swirszcz · Pushmeet Kohli
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #34
Capsule Graph Neural Network
xinyi zhang · Lihui Chen
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #35
ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware
Han Cai · Ligeng Zhu · Song Han
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #36
The Unusual Effectiveness of Averaging in GAN Training
Yasin YAZICI · Chuan-Sheng Foo · Stefan Winkler · Kim-Hui Yap · Georgios Piliouras · Vijay Chandrasekhar
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #37
Understanding and Improving Interpolation in Autoencoders via an Adversarial Regularizer
David Berthelot · Colin Raffel · Aurko Roy · Ian Goodfellow
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #38
Efficient Multi-Objective Neural Architecture Search via Lamarckian Evolution
Thomas Elsken · Jan Metzen · Frank Hutter
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #39
On Self Modulation for Generative Adversarial Networks
Ting Chen · Mario Lucic · Neil Houlsby · Sylvain Gelly
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #40
Building Dynamic Knowledge Graphs from Text using Machine Reading Comprehension
Rajarshi Das · Tsendsuren Munkhdalai · Eric Yuan · Adam Trischler · Andrew McCallum
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #41
Large Scale Graph Learning From Smooth Signals
Vassilis Kalofolias · Nathanaël Perraudin
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #42
Approximability of Discriminators Implies Diversity in GANs
Yu Bai · Tengyu Ma · Andrej Risteski
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #43
On the Sensitivity of Adversarial Robustness to Input Data Distributions
Gavin Ding · Yik Chau Lui · Xiaomeng Jin · Luyu Wang · Ruitong Huang
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #44
Slalom: Fast, Verifiable and Private Execution of Neural Networks in Trusted Hardware
Florian Tramer · Dan Boneh
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #45
GO Gradient for Expectation-Based Objectives
Yulai Cong · Miaoyun Zhao · Ke Bai · Lawrence Carin
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #46
Discriminator Rejection Sampling
Samaneh Azadi · Catherine Olsson · Trevor Darrell · Ian Goodfellow · Augustus Odena
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #47
Don't let your Discriminator be fooled
Brady Zhou · Philipp Krähenbühl
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #48
Supervised Community Detection with Line Graph Neural Networks
Zhengdao Chen · Xiang Li · Joan Bruna
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #49
MisGAN: Learning from Incomplete Data with Generative Adversarial Networks
Steven Cheng-Xian Li · Bo Jiang · Benjamin M Marlin
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #50
Training for Faster Adversarial Robustness Verification via Inducing ReLU Stability
Kai Xiao · Vincent Tjeng · Nur Muhammad Shafiullah · Aleksander Madry
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #51
Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network
Xuanqing Liu · Yao Li · Chongruo Wu · Cho-Jui Hsieh
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #52
Adversarial Imitation via Variational Inverse Reinforcement Learning
Ahmed Qureshi · Byron Boots · Michael C Yip
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #53
Adversarial Attacks on Graph Neural Networks via Meta Learning
Daniel Zügner · Stephan Günnemann
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #54
Prior Convictions: Black-box Adversarial Attacks with Bandits and Priors
Andrew Ilyas · Logan Engstrom · Aleksander Madry
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #55
Defensive Quantization: When Efficiency Meets Robustness
Ji Lin · Chuang Gan · Song Han
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #56
INVASE: Instance-wise Variable Selection using Neural Networks
Jinsung Yoon · James Jordon · Mihaela Schaar
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #57
Scalable Unbalanced Optimal Transport using Generative Adversarial Networks
Karren Yang · Caroline Uhler
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #58
The relativistic discriminator: a key element missing from standard GAN
Alexia Jolicoeur-Martineau
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #59
Are adversarial examples inevitable?
Ali Shafahi · Ronny Huang · Christoph Studer · Soheil Feizi · Tom Goldstein
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #60
Cost-Sensitive Robustness against Adversarial Examples
XIAO ZHANG · David Evans
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #61
RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space
Zhiqing Sun · Zhi-Hong Deng · Jian-Yun Nie · Jian Tang
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #62
Structured Adversarial Attack: Towards General Implementation and Better Interpretability
KAIDI XU · Sijia Liu · Pu Zhao · Pin-Yu Chen · Huan Zhang · Quanfu Fan · Deniz Erdogmus · Yanzhi Wang · Xue Lin
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #63
Adversarial Reprogramming of Neural Networks
Gamaleldin Elsayed · Ian Goodfellow · Jascha Sohl-Dickstein
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #64
Invariant and Equivariant Graph Networks
Haggai Maron · Heli Ben-Hamu · Nadav Shamir · Yaron Lipman
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #65
Excessive Invariance Causes Adversarial Vulnerability
Joern-Henrik Jacobsen · Jens Behrmann · Richard Zemel · Matthias Bethge
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #66
On Computation and Generalization of Generative Adversarial Networks under Spectrum Control
Haoming Jiang · Zhehui Chen · Minshuo Chen · Feng Liu · Dingding Wang · Tuo Zhao
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #67
Dynamic Sparse Graph for Efficient Deep Learning
Liu Liu · Lei Deng · Xing Hu · Maohua Zhu · Guoqi Li · Yufei Ding · Yuan Xie
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #68
SPIGAN: Privileged Adversarial Learning from Simulation
Kuan-Hui Lee · German Ros · Jie Li · Adrien Gaidon
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #69
Towards the first adversarially robust neural network model on MNIST
Lukas Schott · Jonas Rauber · Matthias Bethge · Wieland Brendel
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #70
A Direct Approach to Robust Deep Learning Using Adversarial Networks
huaxia wang · Chun-Nam Yu
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #71
Deep Graph Infomax
Petar Veličković · William Fedus · William L Hamilton · Pietro Liò · Yoshua Bengio · R Devon Hjelm
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #72
Rigorous Agent Evaluation: An Adversarial Approach to Uncover Catastrophic Failures
Jonathan Uesato · Ananya Kumar* · Csaba Szepesvari · Tom Erez · Avraham Ruderman · Keith Anderson · Krishnamurthy Dvijotham · Nicolas Heess · Pushmeet Kohli
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #73
Graph HyperNetworks for Neural Architecture Search
Chris Zhang · Mengye Ren · Raquel Urtasun
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #74
Stochastic Optimization of Sorting Networks via Continuous Relaxations
Aditya Grover · Eric J. Wang · Aaron Zweig · Stefano Ermon
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #75
LayoutGAN: Generating Graphic Layouts with Wireframe Discriminators
Jianan Li · Jimei Yang · Aaron Hertzmann · Jianming Zhang · Tingfa Xu
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #76
DyRep: Learning Representations over Dynamic Graphs
Rakshit Trivedi · Mehrdad Farajtabar · Prasenjeet Biswal · Hongyuan Zha
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #77
Deep reinforcement learning with relational inductive biases
Vinicius Zambaldi · David Raposo · Adam Santoro · Victor Bapst · Yujia Li · Igor Babuschkin · Karl Tuyls · David P Reichert · Timothy Lillicrap · Edward Lockhart · Murray Shanahan · Victoria Langston · Razvan Pascanu · Matthew Botvinick · Oriol Vinyals · Peter Battaglia
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #78
ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness
Robert Geirhos · Patricia Rubisch · Claudio Michaelis · Matthias Bethge · Felix Wichmann · Wieland Brendel
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #79
L-Shapley and C-Shapley: Efficient Model Interpretation for Structured Data
Jianbo Chen · Le Song · Martin Wainwright · Michael Jordan
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #80
Improving the Generalization of Adversarial Training with Domain Adaptation
Chuanbiao Song · Kun He · Liwei Wang · John E Hopcroft
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #81
Sample Efficient Imitation Learning for Continuous Control
Fumihiro Sasaki
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #82
Generalizable Adversarial Training via Spectral Normalization
Farzan Farnia · Jesse Zhang · David Tse
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #83
Learning Latent Superstructures in Variational Autoencoders for Deep Multidimensional Clustering
Xiaopeng Li · Zhourong Chen · Leonard Poon · Nevin Zhang
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #84
DISTRIBUTIONAL CONCAVITY REGULARIZATION FOR GANS
Shoichiro Yamaguchi · Masanori Koyama
Poster
Tue May 7th 04:30 -- 06:30 PM @ Great Hall BC #85
The Limitations of Adversarial Training and the Blind-Spot Attack
Huan Zhang · Hongge Chen · Zhao Song · Duane S Boning · Inderjit Dhillon · Cho-Jui Hsieh
Break
Wed May 8th 08:00 AM -- 06:30 PM @ None
Registration Desk Open
Invited Talk
Wed May 8th 09:00 -- 09:45 AM @ Great Hall AD
Developmental Autonomous Learning: AI, Cognitive Sciences and Educational Technology
Pierre-Yves Oudeyer
Oral
Wed May 8th 09:45 -- 10:00 AM @ Great Hall AD
Learning deep representations by mutual information estimation and maximization
R Devon Hjelm · Alex Fedorov · Samuel Lavoie-Marchildon · Karan Grewal · Philip Bachman · Adam Trischler · Yoshua Bengio
Oral
Wed May 8th 10:00 -- 10:15 AM @ Great Hall AD
KnockoffGAN: Generating Knockoffs for Feature Selection using Generative Adversarial Networks
James Jordon · Jinsung Yoon · Mihaela Schaar
Oral
Wed May 8th 10:15 -- 10:30 AM @ Great Hall AD
Deterministic Variational Inference for Robust Bayesian Neural Networks
Anqi Wu · Sebastian Nowozin · Ted Meeds · Richard E Turner · José Miguel Hernández Lobato · Alexander Gaunt
Oral
Wed May 8th 10:30 -- 10:45 AM @ Great Hall AD
FFJORD: Free-Form Continuous Dynamics for Scalable Reversible Generative Models
Will Grathwohl · Ricky T. Q. Chen · Jesse Bettencourt · Ilya Sutskever · David Duvenaud
Break
Wed May 8th 10:45 -- 11:00 AM @ Hall B-1
Coffee Break
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #1
Soft Q-Learning with Mutual-Information Regularization
Jordi Grau-Moya · Felix Leibfried · Peter Vrancx
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #2
Near-Optimal Representation Learning for Hierarchical Reinforcement Learning
Ofir Nachum · Shixiang Gu · Honglak Lee · Sergey Levine
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #3
Visceral Machines: Risk-Aversion in Reinforcement Learning with Intrinsic Physiological Rewards
Daniel McDuff · Ashish Kapoor
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #4
Knowledge Flow: Improve Upon Your Teachers
Iou-Jen Liu · Jian Peng · Alex Schwing
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #5
Meta-learning with differentiable closed-form solvers
Luca Bertinetto · Joao F. Henriques · Philip Torr · Andrea Vedaldi
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #6
Plan Online, Learn Offline: Efficient Learning and Exploration via Model-Based Control
Kendall Lowrey · Aravind Rajeswaran · Sham M Kakade · Emanuel Todorov · Igor Mordatch
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #7
Probabilistic Planning with Sequential Monte Carlo methods
Alexandre Piche · Valentin Thomas · Cyril Ibrahim · Yoshua Bengio · Christopher Pal
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #8
Directed-Info GAIL: Learning Hierarchical Policies from Unsegmented Demonstrations using Directed Information
Mohit Sharma · Arjun Sharma · Nicholas Rhinehart · Kris M Kitani
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #9
Combinatorial Attacks on Binarized Neural Networks
Elias Khalil · Amrita Gupta · Bistra Dilkina
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #10
Neural Logic Machines
Honghua Dong · Jiayuan Mao · Tian Lin · Chong Wang · Lihong Li · Dengyong Zhou
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #11
Variational Discriminator Bottleneck: Improving Imitation Learning, Inverse RL, and GANs by Constraining Information Flow
Xue Bin Peng · Angjoo Kanazawa · Samuel Toyer · Pieter Abbeel · Sergey Levine
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #12
Two-Timescale Networks for Nonlinear Value Function Approximation
Wesley Chung · Somjit Nath · Ajin Joseph · Martha White
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #13
KnockoffGAN: Generating Knockoffs for Feature Selection using Generative Adversarial Networks
James Jordon · Jinsung Yoon · Mihaela Schaar
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #14
Woulda, Coulda, Shoulda: Counterfactually-Guided Policy Search
Lars Buesing · Theophane Weber · Yori Zwols · Nicolas Heess · Sebastien Racaniere · Arthur Guez · Jean-Baptiste Lespiau
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #15
Competitive experience replay
Hao Liu · Alexander Trott · richard socher · Caiming Xiong
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #17
Multi-step Retriever-Reader Interaction for Scalable Open-domain Question Answering
Rajarshi Das · Shehzaad Dhuliawala · Manzil Zaheer · Andrew McCallum
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #18
Neural Program Repair by Jointly Learning to Localize and Repair
Marko Vasic · Aditya Kanade · Petros Maniatis · David Bieber · Rishabh Singh
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #19
FFJORD: Free-Form Continuous Dynamics for Scalable Reversible Generative Models
Will Grathwohl · Ricky T. Q. Chen · Jesse Bettencourt · Ilya Sutskever · David Duvenaud
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #20
Reasoning About Physical Interactions with Object-Oriented Prediction and Planning
Michael Janner · Sergey Levine · William Freeman · Joshua B Tenenbaum · Chelsea Finn · Jiajun Wu
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #21
M^3RL: Mind-aware Multi-agent Management Reinforcement Learning
Tianmin Shu · Yuandong Tian
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #22
Learning Actionable Representations with Goal Conditioned Policies
Dibya Ghosh · Abhishek Gupta · Sergey Levine
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #23
Neural Graph Evolution: Automatic Robot Design
Tingwu Wang · Yuhao Zhou · Sanja Fidler · Jimmy Ba
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #24
Algorithmic Framework for Model-based Deep Reinforcement Learning with Theoretical Guarantees
Yuping Luo · Huazhe Xu · Yuanzhi Li · Yuandong Tian · Trevor Darrell · Tengyu Ma
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #25
Episodic Curiosity through Reachability
Nikolay Savinov · Anton Raichuk · Damien Vincent · Raphaël Marinier · Marc Pollefeys · Timothy Lillicrap · Sylvain Gelly
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #26
A new dog learns old tricks: RL finds classic optimization algorithms
Weiwei Kong · Christopher Liaw · Aranyak Mehta · D. Sivakumar
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #27
Optimal Completion Distillation for Sequence Learning
Sara Sabour · William Chan · Mohammad Norouzi
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #28
Hierarchical Visuomotor Control of Humanoids
Josh Merel · Arun Ahuja · Vu Pham · Saran Tunyasuvunakool · SIQI LIU · Dhruva Tirumala Bukkapatnam · Nicolas Heess · Greg Wayne
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #29
Meta-Learning For Stochastic Gradient MCMC
Wenbo Gong · Yingzhen Li · José Miguel Hernández Lobato
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #30
Environment Probing Interaction Policies
Wenxuan Zhou · Lerrel Pinto · Abhinav Gupta
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #31
Relational Forward Models for Multi-Agent Learning
Andrea Tacchetti · Francis Song · Pedro Mediano · Vinicius Zambaldi · János Kramár · Neil C Rabinowitz · Thore Graepel · Matthew Botvinick · Peter Battaglia
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #32
Deterministic Variational Inference for Robust Bayesian Neural Networks
Anqi Wu · Sebastian Nowozin · Ted Meeds · Richard E Turner · José Miguel Hernández Lobato · Alexander Gaunt
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #33
Emergent Coordination Through Competition
SIQI LIU · Guy Lever · Josh Merel · Saran Tunyasuvunakool · Nicolas Heess · Thore Graepel
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #34
Variance Reduction for Reinforcement Learning in Input-Driven Environments
Hongzi Mao · Shaileshh Bojja Venkatakrishnan · Malte Schwarzkopf · Mohammad Alizadeh
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #35
A comprehensive, application-oriented study of catastrophic forgetting in DNNs
Benedikt Pfülb · Alexander Gepperth
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #36
Information asymmetry in KL-regularized RL
Alexandre Galashov · Siddhant Jayakumar · Leonard Hasenclever · Dhruva Tirumala Bukkapatnam · Jonathan Schwarz · Guillaume Desjardins · Wojciech M Czarnecki · Yee Whye Teh · Razvan Pascanu · Nicolas Heess
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #37
Modeling the Long Term Future in Model-Based Reinforcement Learning
Nan Rosemary Ke · Amanpreet Singh · Ahmed Touati · Anirudh Goyal Alias Parth Goyal · Yoshua Bengio · Devi Parikh · Dhruv Batra
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #38
Synthetic Datasets for Neural Program Synthesis
Richard Shin · Neel Kant · Kavi Gupta · Christopher Bender · Brandon Trabucco · Rishabh Singh · Dawn Song
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #39
Unsupervised Learning via Meta-Learning
Kyle Hsu · Sergey Levine · Chelsea Finn
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #40
Learning to Navigate the Web
Izzeddin Gur · Ulrich Rueckert · Aleksandra Faust · Dilek Hakkani-Tur
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #41
Marginal Policy Gradients: A Unified Family of Estimators for Bounded Action Spaces with Applications
Carson Eisenach · Haichuan Yang · Ji Liu · Han Liu
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #42
Sample Efficient Adaptive Text-to-Speech
Yutian Chen · Yannis M Assael · Brendan Shillingford · David Budden · Scott Reed · Heiga Zen · Quan Wang · Luis C. Cobo · Andrew Trask · Ben Laurie · Caglar Gulcehre · Aaron van den Oord · Oriol Vinyals · Nando de Freitas
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #43
CEM-RL: Combining evolutionary and gradient-based methods for policy search
Aloïs Pourchot · Olivier Sigaud
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #44
An Empirical Study of Example Forgetting during Deep Neural Network Learning
Mariya Toneva · Alessandro Sordoni · Remi Combes · Adam Trischler · Yoshua Bengio · Geoffrey Gordon
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #45
Learning Multi-Level Hierarchies with Hindsight
Andrew Levy · George D Konidaris · Robert Platt · Kate Saenko
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #46
Reward Constrained Policy Optimization
Chen Tessler · Daniel J Mankowitz · Shie Mannor
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #47
Learning when to Communicate at Scale in Multiagent Cooperative and Competitive Tasks
Amanpreet Singh · Tushar Jain · Sainbayar Sukhbaatar
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #48
Supervised Policy Update for Deep Reinforcement Learning
Quan Vuong · Yiming Zhang · Keith Ross
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #49
Towards Metamerism via Foveated Style Transfer
Arturo Deza · Aditya Jonnalagadda · Miguel Eckstein
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #50
Deep Online Learning Via Meta-Learning: Continual Adaptation for Model-Based RL
Anusha Nagabandi · Chelsea Finn · Sergey Levine
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #51
Probabilistic Recursive Reasoning for Multi-Agent Reinforcement Learning
Ying Wen · Yaodong Yang · Rui Luo · Jun Wang · Wei Pan
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #52
Analysing Mathematical Reasoning Abilities of Neural Models
David Saxton · Edward Grefenstette · Felix Hill · Pushmeet Kohli
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #53
Execution-Guided Neural Program Synthesis
Xinyun Chen · Chang Liu · Dawn Song
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #54
Learning deep representations by mutual information estimation and maximization
R Devon Hjelm · Alex Fedorov · Samuel Lavoie-Marchildon · Karan Grewal · Philip Bachman · Adam Trischler · Yoshua Bengio
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #55
Meta-Learning Probabilistic Inference for Prediction
Jonathan Gordon · John Bronskill · Matthias Bauer · Sebastian Nowozin · Richard E Turner
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #56
Solving the Rubik's Cube with Approximate Policy Iteration
Stephen McAleer · Forest Agostinelli · Alexander K Shmakov · Pierre Baldi
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #57
Universal Successor Features Approximators
Diana Borsa · Andre Barreto · John Quan · Daniel J Mankowitz · Hado van Hasselt · Remi Munos · David Silver · Tom Schaul
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #58
Information-Directed Exploration for Deep Reinforcement Learning
Nikolay Nikolov · Johannes Kirschner · Felix Berkenkamp · Andreas Krause
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #59
Learning Exploration Policies for Navigation
Tao Chen · Saurabh Gupta · Abhinav Gupta
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #60
Hindsight policy gradients
Paulo Rauber · Avinash Ummadisingu · Filipe Mutz · Jürgen Schmidhuber
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #61
ProMP: Proximal Meta-Policy Search
Jonas Rothfuss · Dennis Lee · Ignasi Clavera · Tamim Asfour · Pieter Abbeel
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #62
AutoLoss: Learning Discrete Schedule for Alternate Optimization
Haowen Xu · Hao Zhang · Zhiting Hu · Xiaodan Liang · Ruslan Salakhutdinov · Eric Xing
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #63
Neural Probabilistic Motor Primitives for Humanoid Control
Josh Merel · Leonard Hasenclever · Alexandre Galashov · Arun Ahuja · Vu Pham · Greg Wayne · Yee Whye Teh · Nicolas Heess
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #64
How to train your MAML
Antreas Antoniou · Harrison Edwards · Amos Storkey
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #65
Adaptive Posterior Learning: few-shot learning with a surprise-based memory module
Tiago Ramalho · Marta Garnelo
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #67
The Laplacian in RL: Learning Representations with Efficient Approximations
Yifan Wu · George Tucker · Ofir Nachum
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #68
Exploration by random network distillation
Yuri Burda · Harrison Edwards · Amos Storkey · Oleg Klimov
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #69
Composing Complex Skills by Learning Transition Policies
Youngwoon Lee · Shao-Hua Sun · Sriram Somasundaram · Edward S Hu · Joseph Lim
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #70
Hierarchical RL Using an Ensemble of Proprioceptive Periodic Policies
Kenneth Marino · Abhinav Gupta · Rob Fergus · Arthur Szlam
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #71
Measuring and regularizing networks in function space
Ari S Benjamin · David Rolnick · Konrad P Kording
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #72
Learning to Schedule Communication in Multi-agent Reinforcement Learning
Daewoo Kim · Sangwoo Moon · David Earl Hostallero · Wan Ju Kang · Taeyoung Lee · Kyunghwan Son · Yung Yi
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #73
LEARNING TO PROPAGATE LABELS: TRANSDUCTIVE PROPAGATION NETWORK FOR FEW-SHOT LEARNING
Yanbin Liu · Juho Lee · Minseop Park · Saehoon Kim · Eunho Yang · Sung Ju Hwang · Yi Yang
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #74
NADPEx: An on-policy temporally consistent exploration method for deep reinforcement learning
Sirui Xie · Junning Huang · Lanxin Lei · Chunxiao Liu · Zheng Ma · Wei Zhang · Liang Lin
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #75
Policy Transfer with Strategy Optimization
Wenhao Yu · C. Liu · Greg Turk
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #76
Large-Scale Study of Curiosity-Driven Learning
Yuri Burda · Harrison Edwards · Deepak Pathak · Amos Storkey · Trevor Darrell · Alexei Efros
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #77
Diversity is All You Need: Learning Skills without a Reward Function
Benjamin Eysenbach · Abhishek Gupta · Julian Ibarz · Sergey Levine
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #78
Preferences Implicit in the State of the World
Rohin Shah · Dmitrii Krasheninnikov · Jordan Alexander · Pieter Abbeel · Anca Dragan
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #79
Learning to Learn with Conditional Class Dependencies
Xiang Jiang · Seyed Mohammad Havaei · Farshid Varno · Gabriel Chartrand · Nicolas Chapados · Stan Matwin
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #80
Hierarchical Reinforcement Learning via Advantage-Weighted Information Maximization
Takayuki Osa · Voot Tangkaratt · Masashi Sugiyama
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #81
Efficient Lifelong Learning with A-GEM
Arslan Chaudhry · Marc'Aurelio Ranzato · Marcus Rohrbach · Mohamed Elhoseiny
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #82
Learning to Learn without Forgetting by Maximizing Transfer and Minimizing Interference
Matt Riemer · Juan Ignacio Cases Martin · Robert Ajemian · Miao Liu · Irina Rish · Yuhai Tu · Gerald Tesauro
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #83
Automatically Composing Representation Transformations as a Means for Generalization
Michael Chang · Abhishek Gupta · Sergey Levine · Thomas L Griffiths
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #84
Contingency-Aware Exploration in Reinforcement Learning
Jongwook Choi · Yijie Guo · Marcin Moczulski · Junhyuk Oh · Neal Wu · Mohammad Norouzi · Honglak Lee
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #85
Overcoming Catastrophic Forgetting for Continual Learning via Model Adaptation
Wenpeng Hu · Zhou Lin · Bing Liu · Chongyang Tao · Jay Tao · Jinwen Ma · Dongyan Zhao · Rui Yan
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #86
A Closer Look at Few-shot Classification
Wei-Yu Chen · Yen-Cheng Liu · Zsolt Kira · Yu-Chiang Frank Wang · Jia-Bin Huang
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #87
On Random Deep Weight-Tied Autoencoders: Exact Asymptotic Analysis, Phase Transitions, and Implications to Training
Ping Li · Phan-Minh Nguyen
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #88
Discriminator-Actor-Critic: Addressing Sample Inefficiency and Reward Bias in Adversarial Imitation Learning
Ilya Kostrikov · Kumar Agrawal · Debidatta Dwibedi · Sergey Levine · Jonathan Tompson
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #89
Opportunistic Learning: Budgeted Cost-Sensitive Learning from Data Streams
Mohammad Kachuee · Orpaz Goldstein · Kimmo Kärkkäinen · Sajad Darabi · Majid Sarrafzadeh
Poster
Wed May 8th 11:00 AM -- 01:00 PM @ Great Hall BC #90
Selfless Sequential Learning
Rahaf Aljundi · Marcus Rohrbach · Tinne Tuytelaars
Break
Wed May 8th 01:00 -- 02:30 PM @ on your own
Lunch - on your own
Invited Talk
Wed May 8th 02:30 -- 03:15 PM @ Great Hall AD
While We're All Worried about Failures of Machine Learning, What Dangers Lurk If It (Mostly) Works?
Zeynep Tufekci
Oral
Wed May 8th 03:15 -- 04:15 PM @ None
ICLR Debate
Leslie Kaelbling
Break
Wed May 8th 04:15 -- 04:30 PM @ Hall B-1
Coffee Break
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #1
AdaShift: Decorrelation and Convergence of Adaptive Learning Rate Methods
Zhiming Zhou · Qingru Zhang · Guansong Lu · Hongwei Wang · Weinan Zhang · Yong Yu
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #2
Self-Tuning Networks: Bilevel Optimization of Hyperparameters using Structured Best-Response Functions
Matthew MacKay · Paul Vicol · Jonathan Lorraine · David Duvenaud · Roger Grosse
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #3
G-SGD: Optimizing ReLU Neural Networks in its Positively Scale-Invariant Space
Qi Meng · Shuxin Zheng · Huishuai Zhang · Wei Chen · Qiwei Ye · Zhi-Ming Ma · Nenghai Yu · Tie-Yan Liu
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #4
Learning to Make Analogies by Contrasting Abstract Relational Structure
Felix Hill · Adam Santoro · David GT Barrett · Ari Morcos · Timothy Lillicrap
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #5
Deep Frank-Wolfe For Neural Network Optimization
Leonard Berrada · Andrew Zisserman · M. Pawan Kumar
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #6
Off-Policy Evaluation and Learning from Logged Bandit Feedback: Error Reduction via Surrogate Policy
Yuan Xie · Boyi Liu · Qiang Liu · Zhaoran Wang · Yuan Zhou · Jian Peng
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #7
A2BCD: Asynchronous Acceleration with Optimal Complexity
Robert Hannah · Fei Feng · Wotao Yin
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #8
An analytic theory of generalization dynamics and transfer learning in deep linear networks
Andrew Lampinen · Surya Ganguli
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #9
Minimal Random Code Learning: Getting Bits Back from Compressed Model Parameters
Marton Havasi · Robert Peharz · José Miguel Hernández Lobato
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #10
ANYTIME MINIBATCH: EXPLOITING STRAGGLERS IN ONLINE DISTRIBUTED OPTIMIZATION
Nuwan Ferdinand · Haider Al-Lawati · Stark Draper · Matthew Nokleby
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #11
Towards Understanding Regularization in Batch Normalization
Ping Luo · Xinjiang Wang · wenqi shao · Zhanglin Peng
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #12
A Mean Field Theory of Batch Normalization
Greg Yang · Jeffrey Pennington · Vinay Rao · Jascha Sohl-Dickstein · Samuel S Schoenholz
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #13
Predicting the Generalization Gap in Deep Networks with Margin Distributions
YiDing Jiang · Dilip Krishnan · Hossein Mobahi · Samy Bengio
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #14
An Empirical study of Binary Neural Networks' Optimisation
Milad Alizadeh · Javier Fernández Marqués · Nicholas Lane · Yarin Gal
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #15
Deterministic PAC-Bayesian generalization bounds for deep networks via generalizing noise-resilience
Vaishnavh Nagarajan · Zico Kolter
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #16
Efficient Training on Very Large Corpora via Gramian Estimation
Walid Krichene · Nicolas Mayoraz · Steffen Rendle · Li Zhang · Xinyang Yi · Lichan Hong · Ed H. Chi · John Anderson
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #17
Small nonlinearities in activation functions create bad local minima in neural networks
Chulhee Yun · Suvrit Sra · Ali Jadbabaie
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #18
Fluctuation-dissipation relations for stochastic gradient descent
Sho Yaida
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #20
The Comparative Power of ReLU Networks and Polynomial Kernels in the Presence of Sparse Latent Structure
Frederic Koehler · Andrej Risteski
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #21
Optimal Control Via Neural Networks: A Convex Approach
Yize Chen · Yuanyuan Shi · Baosen Zhang
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #22
NOODL: Provable Online Dictionary Learning and Sparse Coding
Sirisha Rambhatla · Xingguo Li · Jarvis Haupt
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #23
Energy-Constrained Compression for Deep Neural Networks via Weighted Sparse Projection and Layer Input Masking
Haichuan Yang · Yuhao Zhu · Ji Liu
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #24
SGD Converges to Global Minimum in Deep Learning via Star-convex Path
Yi Zhou · Junjie Yang · Huishuai Zhang · Yingbin Liang · VAHID TAROKH
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #25
Deep Lagrangian Networks: Using Physics as Model Prior for Deep Learning
Michael Lutter · Christian Ritter · Jan Peters
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #26
Relaxed Quantization for Discretized Neural Networks
Christos Louizos · Matthias Reisser · Tijmen Blankevoort · Efstratios Gavves · Max Welling
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #27
There Are Many Consistent Explanations of Unlabeled Data: Why You Should Average
Ben Athiwaratkun · Marc A Finzi · Pavel Izmailov · Andrew G Wilson
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #28
signSGD with Majority Vote is Communication Efficient and Fault Tolerant
Jeremy Bernstein · Jiawei Zhao · Kamyar Azizzadenesheli · Anima Anandkumar
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #29
Preconditioner on Matrix Lie Group for SGD
XI-LIN LI
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #30
A Closer Look at Deep Learning Heuristics: Learning rate restarts, Warmup and Distillation
Akhilesh Deepak Gotmare · Nitish Shirish Keskar · Caiming Xiong · richard socher
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #31
Max-MIG: an Information Theoretic Approach for Joint Learning from Crowds
Peng Cao · Yilun Xu · Yuqing Kong · Yizhou Wang
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #32
Rethinking the Value of Network Pruning
Zhuang Liu · Mingjie Sun · Tinghui Zhou · Gao Huang · Trevor Darrell
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #33
Learning Embeddings into Entropic Wasserstein Spaces
Charlie Frogner · Farzaneh Mirzazadeh · Justin Solomon
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #34
Deep Layers as Stochastic Solvers
Adel Bibi · Bernard Ghanem · Vladlen Koltun · Rene Ranftl
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #35
Initialized Equilibrium Propagation for Backprop-Free Training
Peter OConnor · Efstratios Gavves · Max Welling
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #36
Caveats for information bottleneck in deterministic scenarios
Artemy Kolchinsky · Brendan D Tracey · Steven Van Kuyk
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #37
Learning Two-layer Neural Networks with Symmetric Inputs
Rong Ge · Rohith Kuditipudi · Zhize Li · Xiang Wang
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #38
Sparse Dictionary Learning by Dynamical Neural Networks
Tsung-Han Lin · Ping Tak P Tang
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #39
Universal Stagewise Learning for Non-Convex Problems with Convergence on Averaged Solutions
Zaiyi Chen · Zhuoning Yuan · Jinfeng Yi · Bowen Zhou · Enhong Chen · Tianbao Yang
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #40
Gradient descent aligns the layers of deep linear networks
Ziwei Ji · Matus Telgarsky
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #41
Stochastic Gradient/Mirror Descent: Minimax Optimality and Implicit Regularization
Navid Azizan · Babak Hassibi
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #42
Learning Self-Imitating Diverse Policies
Tanmay Gangwani · Qiang Liu · Jian Peng
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #43
On the Universal Approximability and Complexity Bounds of Quantized ReLU Neural Networks
Yukun Ding · Jinglan Liu · Jinjun Xiong · Yiyu Shi
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #44
Adaptive Gradient Methods with Dynamic Bound of Learning Rate
Liangchen Luo · Yuanhao Xiong · Yan Liu · Xu Sun
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #45
Slimmable Neural Networks
Jiahui Yu · Linjie Yang · Ning Xu · Jianchao Yang · Thomas Huang
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #46
Per-Tensor Fixed-Point Quantization of the Back-Propagation Algorithm
Charbel Sakr · Naresh Shanbhag
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #47
The role of over-parametrization in generalization of neural networks
Behnam Neyshabur · Zhiyuan Li · Srinadh Bhojanapalli · Yann LeCun · Nathan Srebro
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #48
Data-Dependent Coresets for Compressing Neural Networks with Applications to Generalization Bounds
Cenk Baykal · Lucas Liebenwein · Igor Gilitschenski · Dan Feldman · Daniela Rus
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #50
Understanding Straight-Through Estimator in Training Activation Quantized Neural Nets
Penghang Yin · Jiancheng Lyu · shuai zhang · Stanley J Osher · YINGYONG QI · Jack Xin
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #51
Learning concise representations for regression by evolving networks of trees
William La Cava · Tilak Raj Singh · Srinivas Suri · Srinivas Suri
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #52
Optimistic mirror descent in saddle-point problems: Going the extra (gradient) mile
Panayotis Mertikopoulos · Bruno Lecouat · Houssam Zenati · Chuan-Sheng Foo · Vijay Chandrasekhar · Georgios Piliouras
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #53
ACCELERATING NONCONVEX LEARNING VIA REPLICA EXCHANGE LANGEVIN DIFFUSION
Yi Chen · Jinglin Chen · Jing Dong · Jian Peng · Zhaoran Wang
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #54
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks
Jonathan Frankle · Michael Carbin
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #55
Three Mechanisms of Weight Decay Regularization
Guodong Zhang · Chaoqi Wang · Bowen Xu · Roger Grosse
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #56
Double Viterbi: Weight Encoding for High Compression Ratio and Fast On-Chip Reconstruction for Deep Neural Network
Daehyun Ahn · Dongsoo Lee · Taesu Kim · Jae-Joon Kim
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #57
Quasi-hyperbolic momentum and Adam for deep learning
Jerry Ma · Denis Yarats
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #58
Towards Robust, Locally Linear Deep Networks
Guang-He Lee · David Alvarez-Melis · Tommi Jaakkola
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #59
InfoBot: Transfer and Exploration via the Information Bottleneck
Anirudh Goyal Alias Parth Goyal · Riashat Islam · DJ Strouse · Zafarali Ahmed · Hugo Larochelle · Matthew Botvinick · Sergey Levine · Yoshua Bengio
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #61
Aggregated Momentum: Stability Through Passive Damping
James Lucas · Shengyang Sun · Richard Zemel · Roger Grosse
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #62
From Hard to Soft: Understanding Deep Network Nonlinearities via Vector Quantization and Statistical Inference
Randall Balestriero · Richard Baraniuk
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #63
Riemannian Adaptive Optimization Methods
Gary Bécigneul · Octavian Ganea
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #64
Regularized Learning for Domain Adaptation under Label Shifts
Kamyar Azizzadenesheli · Anqi Liu · Fanny Yang · Anima Anandkumar
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #65
DeepOBS: A Deep Learning Optimizer Benchmark Suite
Frank Stefan Schneider · Lukas Balles · Philipp Hennig
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #66
Fixup Initialization: Residual Learning Without Normalization
Hongyi Zhang · Yann Dauphin · Tengyu Ma
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #67
Learning sparse relational transition models
Victoria Xia · Zi Wang · Kelsey Allen · Tom Silver · Leslie Kaelbling
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #68
Gradient Descent Provably Optimizes Over-parameterized Neural Networks
Simon Du · Xiyu Zhai · Barnabás Póczos · Aarti Singh
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #69
On the Relation Between the Sharpest Directions of DNN Loss and the SGD Step Length
Stanislaw Jastrzebski · Zachary Kenton · Nicolas Ballas · Asja Fischer · Yoshua Bengio · Amos Storkey
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #70
A Kernel Random Matrix-Based Approach for Sparse PCA
Mohamed El Amine Seddik · mohamed Tamaazousti · Romain Couillet
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #71
SNIP: SINGLE-SHOT NETWORK PRUNING BASED ON CONNECTION SENSITIVITY
Namhoon Lee · Thalaiyasingam Ajanthan · Philip H.S Torr
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #72
Critical Learning Periods in Deep Networks
Alessandro Achille · Matteo Rovere · Stefano Soatto
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #73
Local SGD Converges Fast and Communicates Little
Sebastian Stich
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #74
Adaptivity of deep ReLU network for learning in Besov and mixed smooth Besov spaces: optimal rate and curse of dimensionality
Taiji Suzuki
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #75
A Convergence Analysis of Gradient Descent for Deep Linear Neural Networks
Sanjeev Arora · Nadav Cohen · Noah Golowich · Wei Hu
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #76
Analysis of Quantized Models
LU HOU · Ruiliang Zhang · James Kwok
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #77
Adaptive Estimators Show Information Compression in Deep Neural Networks
Ivan Chelombiev · Conor Houghton · Cian O'Donnell
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #78
On the Convergence of A Class of Adam-Type Algorithms for Non-Convex Optimization
Xiangyi Chen · Sijia Liu · Ruoyu Sun · Mingyi Hong
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #79
Theoretical Analysis of Auto Rate-Tuning by Batch Normalization
Sanjeev Arora · Zhiyuan Li · Kaifeng Lyu
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #80
Decoupled Weight Decay Regularization
Ilya Loshchilov · Frank Hutter
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #81
ALISTA: Analytic Weights Are As Good As Learned Weights in LISTA
Jialin Liu · Xiaohan Chen · Zhangyang Wang · Wotao Yin
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #82
Query-Efficient Hard-label Black-box Attack: An Optimization-based Approach
Minhao Cheng · Thong M Le · Pin-Yu Chen · Huan Zhang · Jinfeng Yi · Cho-Jui Hsieh
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #83
Minimum Divergence vs. Maximum Margin: an Empirical Comparison on Seq2Seq Models
Huan Zhang · hai zhao
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #84
Subgradient Descent Learns Orthogonal Dictionaries
Yu Bai · Qijia Jiang · Ju Sun
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #85
ProxQuant: Quantized Neural Networks via Proximal Operators
Yu Bai · Yu-Xiang Wang · Edo Liberty
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #86
Systematic Generalization: What Is Required and Can It Be Learned?
Dzmitry Bahdanau · Shikhar Murty · Mikhail Noukhovitch · Thien H Nguyen · Harm de Vries · Aaron Courville
Poster
Wed May 8th 04:30 -- 06:30 PM @ Great Hall BC #87
Deep Anomaly Detection with Outlier Exposure
Dan Hendrycks · Mantas Mazeika · Thomas Dietterich
Break
Thu May 9th 08:00 AM -- 12:00 PM @ None
Registration Desk Open
Invited Talk
Thu May 9th 09:00 -- 09:45 AM @ Great Hall AD
Learning Natural Language Interfaces with Neural Models
Mirella Lapata
Oral
Thu May 9th 09:45 -- 10:00 AM @ Great Hall AD
Pay Less Attention with Lightweight and Dynamic Convolutions
Felix Wu · Angela Fan · Alexei Baevski · Yann Dauphin · Michael Auli
Oral
Thu May 9th 10:00 -- 10:15 AM @ Great Hall AD
The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural Supervision
Jiayuan Mao · Chuang Gan · Pushmeet Kohli · Joshua B Tenenbaum · Jiajun Wu
Oral
Thu May 9th 10:15 -- 10:30 AM @ Great Hall AD
Smoothing the Geometry of Probabilistic Box Embeddings
Xiang Li · Luke Vilnis · Dongxu Zhang · Michael Boratko · Andrew McCallum
Break
Thu May 9th 10:30 -- 11:00 AM @ Hall B-1
Coffee Break (Rescheduled from 10:30 to 10:45)
Oral
Thu May 9th 10:30 -- 10:45 AM @ Great Hall AD
Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks
Yikang Shen · Shawn Tan · Alessandro Sordoni · Aaron Courville
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #1
CBOW Is Not All You Need: Combining CBOW with the Compositional Matrix Space Model
Florian Mai · Lukas Galke · Ansgar Scherp
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #2
Kernel RNN Learning (KeRNL)
Christopher Roth · Ingmar Kanitscheider · Ila Fiete
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #3
Unsupervised Hyper-alignment for Multilingual Word Embeddings
Jean Alaux-Lorain · Edouard Grave · marco cuturi · Armand Joulin
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #4
textTOvec: DEEP CONTEXTUALIZED NEURAL AUTOREGRESSIVE TOPIC MODELS OF LANGUAGE WITH DISTRIBUTED COMPOSITIONAL PRIOR
Pankaj Gupta · Yatin Chaudhary · Florian Buettner · Hinrich Schuetze
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #5
Coarse-grain Fine-grain Coattention Network for Multi-evidence Question Answering
Victor Zhong · Caiming Xiong · Nitish Shirish Keskar · richard socher
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #6
Generalized Tensor Models for Recurrent Neural Networks
Valentin Khrulkov · Oleksii Hrinchuk · Ivan Oseledets
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #7
Representing Formal Languages: A Comparison Between Finite Automata and Recurrent Neural Networks
Joshua Michalenko · Ameesh Shah · Abhinav Verma · Richard Baraniuk · Swarat Chaudhuri · Ankit B Patel
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #8
Top-Down Neural Model For Formulae
Karel Chvalovský
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #9
Variational Smoothing in Recurrent Neural Network Language Models
Lingpeng Kong · Gábor Melis · Wang Ling · Lei Yu · Dani Yogatama
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #10
Large-Scale Answerer in Questioner's Mind for Visual Dialog Question Generation
Sang-Woo Lee · Tong Gao · Sohee Yang · Jaejun Yoo · Jung-Woo Ha
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #11
DOM-Q-NET: Grounded RL on Structured Language
Sheng Jia · Jamie Kiros · Jimmy Ba
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #12
Poincare Glove: Hyperbolic Word Embeddings
Alexandru Tifrea · Gary Bécigneul · Octavian Ganea
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #13
Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks
Yikang Shen · Shawn Tan · Alessandro Sordoni · Aaron Courville
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #14
Learning Recurrent Binary/Ternary Weights
Arash Ardakani · Zhengyun Ji · Sean Smithson · Brett Meyer · Warren J Gross
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #15
FlowQA: Grasping Flow in History for Conversational Machine Comprehension
Hsin-Yuan Huang · Eunsol Choi · Wen-tau Yih
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #16
Differentiable Perturb-and-Parse: Semi-Supervised Parsing with a Structured Variational Autoencoder
Caio Corro · Ivan Titov
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #17
Adaptive Input Representations for Neural Language Modeling
Alexei Baevski · Michael Auli
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #18
Neural Speed Reading with Structural-Jump-LSTM
Christian Hansen · Casper Hansen · Stephen Alstrup · Jakob Simonsen · Christina Lioma
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #19
Tree-Structured Recurrent Switching Linear Dynamical Systems for Multi-Scale Modeling
Josue Nassar · Scott W Linderman · Monica Bugallo · Il M Park
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #20
Multilingual Neural Machine Translation with Knowledge Distillation
Xu Tan · Yi Ren · Di He · Tao Qin · Zhou Zhao · Tie-Yan Liu
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #21
h-detach: Modifying the LSTM Gradient Towards Better Optimization
Bhargav Kanuparthi · Devansh Arpit · Giancarlo Kerg · Nan Rosemary Ke · Ioannis Mitliagkas · Yoshua Bengio
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #23
Multiple-Attribute Text Rewriting
Guillaume Lample · Sandeep Subramanian · Eric Smith · Ludovic Denoyer · Marc'Aurelio Ranzato · Y-Lan Boureau
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #24
RNNs implicitly implement tensor-product representations
Tom McCoy · Tal Linzen · Ewan Dunbar · Paul Smolensky
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #25
Complement Objective Training
Hao-Yun Chen · Pei-Hsin Wang · Chun-Hao Liu · Shih-Chieh Chang · Jia-Yu Pan · Yu-Ting Chen · Wei Wei · Da-Cheng Juan
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #26
Adversarial Audio Synthesis
Chris Donahue · Julian McAuley · Miller Puckette
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #27
A Generative Model For Electron Paths
John Bradshaw · Matt Kusner · Brooks Paige · Marwin Segler · José Miguel Hernández Lobato
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #28
Smoothing the Geometry of Probabilistic Box Embeddings
Xiang Li · Luke Vilnis · Dongxu Zhang · Michael Boratko · Andrew McCallum
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #29
Wizard of Wikipedia: Knowledge-Powered Conversational Agents
Emily Dinan · Stephen Roller · Kurt Shuster · Angela Fan · Michael Auli · Jason Weston
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #30
Understanding Composition of Word Embeddings via Tensor Decomposition
Abraham Frandsen · Rong Ge
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #31
Multilingual Neural Machine Translation With Soft Decoupled Encoding
Xinyi Wang · Hieu Pham · Philip Arthur · Graham Neubig
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #32
The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural Supervision
Jiayuan Mao · Chuang Gan · Pushmeet Kohli · Joshua B Tenenbaum · Jiajun Wu
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #33
Characterizing Audio Adversarial Examples Using Temporal Dependency
Zhuolin Yang · Bo Li · Pin-Yu Chen · Dawn Song
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #34
Harmonic Unpaired Image-to-image Translation
Rui Zhang · Tomas Pfister · Li-Jia Li
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #35
Backpropamine: training self-modifying neural networks with differentiable neuromodulated plasticity
Thomas Miconi · Aditya Rawal · Jeff Clune · Kenneth O. Stanley
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #36
Learning Implicitly Recurrent CNNs Through Parameter Sharing
Pedro Henrique Pamplona Savarese · Michael Maire
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #37
Identifying and Controlling Important Neurons in Neural Machine Translation
David A Bau · Yonatan Belinkov · Hassan Sajjad · Nadir Durrani · Fahim Dalvi · James R Glass
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #38
Learning Finite State Representations of Recurrent Policy Networks
Anurag Koul · Alan Fern · Samuel Greydanus
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #39
AntisymmetricRNN: A Dynamical System View on Recurrent Neural Networks
Bo Chang · Minmin Chen · Eldad Haber · Ed H. Chi
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #40
Learning protein sequence embeddings using information from structure
Tristan Bepler · Bonnie Berger
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #41
Unsupervised Speech Recognition via Segmental Empirical Output Distribution Matching
Chih-Kuan Yeh · Jianshu Chen · Chengzhu Yu · Dong Yu
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #42
Von Mises-Fisher Loss for Training Sequence to Sequence Models with Continuous Outputs
Sachin Kumar · Yulia Tsvetkov
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #43
Transfer Learning for Sequences via Learning to Collocate
Wanyun Cui · Guangyu Zheng · Zhiqiang Shen · Sihang Jiang · Wei Wang
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #44
Hyperbolic Attention Networks
Caglar Gulcehre · Misha Denil · Mateusz Malinowski · Ali Razavi · Razvan Pascanu · Karl Moritz Hermann · Victor Bapst · Victor Bapst · Adam Santoro · Nando de Freitas
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #45
Hierarchical interpretations for neural network predictions
Chandan Singh · William Murdoch · Bin Yu
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #46
Hierarchical Generative Modeling for Controllable Speech Synthesis
Wei-Ning Hsu · Yu Zhang · Ron Weiss · Heiga Zen · Yonghui Wu · Yuxuan Wang · Yuan Cao · Ye Jia · Zhifeng Chen · Jonathan Shen · Patrick Nguyen · Ruoming Pang
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #47
Learning what and where to attend
Drew Linsley · Dan Shiebler · Sven Eberhardt · Thomas Serre
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #48
Discovery of Natural Language Concepts in Individual Units of CNNs
Seil Na · Yo Joong Choe · Dong-Hyun Lee · Gunhee Kim
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #49
Posterior Attention Models for Sequence to Sequence Learning
Shiv Shankar · Sunita Sarawagi
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #50
Don't Settle for Average, Go for the Max: Fuzzy Sets and Max-Pooled Word Vectors
Vitalii Zhelezniak · Aleksandar D Savkov · April Shen · Francesco Moramarco · Jack Flann · Nils Hammerla
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #51
Learning to Represent Edits
Pengcheng Yin · Graham Neubig · Miltiadis Allamanis · Marc Brockschmidt · Alexander Gaunt
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #52
What do you learn from context? Probing for sentence structure in contextualized word representations
Ian Tenney · Patrick Xia · Berlin Chen · Alex Wang · Adam Poliak · Tom McCoy · Najoung Kim · Benjamin Van Durme · Samuel R. Bowman · Dipanjan Das · Ellie Pavlick
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #53
Music Transformer: Generating Music with Long-Term Structure
Anna Huang · Ashish Vaswani · Jakob Uszkoreit · Ian Simon · Curtis Hawthorne · Noam Shazeer · Andrew Dai · Matthew D Hoffman · Monica Dinculescu · Douglas Eck
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #54
Representation Degeneration Problem in Training Natural Language Generation Models
Jun Gao · Di He · Xu Tan · Tao Qin · Liwei Wang · Tie-Yan Liu
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #55
Detecting Egregious Responses in Neural Sequence-to-sequence Models
Tianxing He · James R Glass
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #56
Learning to Design RNA
Frederic Runge · Danny Stoll · Stefan Falkner · Frank Hutter
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #57
Dynamically Unfolding Recurrent Restorer: A Moving Endpoint Control Method for Image Restoration
Xiaoshuai Zhang · Yiping Lu · Jiaying Liu · Bin Dong
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #58
Imposing Category Trees Onto Word-Embeddings Using A Geometric Construction
Tiansi Dong · Christian Bauckhage · Hailong Jin · Juanzi Li · Olaf Cremers · Daniel Speicher · Armin Cremers · Joerg Zimmermann
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #59
Multi-Agent Dual Learning
Yiren Wang · Yingce Xia · Tianyu He · Fei Tian · Tao Qin · ChengXiang Zhai · Tie-Yan Liu
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #61
Trellis Networks for Sequence Modeling
Shaojie Bai · Zico Kolter · Vladlen Koltun
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #62
Universal Transformers
Mostafa Dehghani · Stephan Gouws · Oriol Vinyals · Jakob Uszkoreit · Lukasz Kaiser
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #63
Structured Neural Summarization
Patrick Fernandes · Miltiadis Allamanis · Marc Brockschmidt
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #64
Global-to-local Memory Pointer Networks for Task-Oriented Dialogue
Chien-Sheng Wu · richard socher · Caiming Xiong
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #65
From Language to Goals: Inverse Reinforcement Learning for Vision-Based Instruction Following
Justin Fu · Anoop Korattikara Balan · Sergey Levine · Sergio Guadarrama
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #66
A Universal Music Translation Network
Noam Mor · Lior Wolf · Adam Polyak · Yaniv Taigman
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #67
Guiding Policies with Language via Meta-Learning
John Co-Reyes · Abhishek Gupta · Suvansh Sanjeev · Nicholas Altieri · Jacob Andreas · John DeNero · Pieter Abbeel · Sergey Levine
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #68
Recurrent Experience Replay in Distributed Reinforcement Learning
Steven Kapturowski · Georg Ostrovski · John Quan · Remi Munos · Will Dabney
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #69
Learning Multimodal Graph-to-Graph Translation for Molecule Optimization
Wengong Jin · Kevin Yang · Regina Barzilay · Tommi Jaakkola
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #70
Stable Recurrent Models
John Miller · Moritz Hardt
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #71
DARTS: Differentiable Architecture Search
Hanxiao Liu · Karen Simonyan · Yiming Yang
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #72
Pay Less Attention with Lightweight and Dynamic Convolutions
Felix Wu · Angela Fan · Alexei Baevski · Yann Dauphin · Michael Auli
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #73
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding
Alex Wang · Amanpreet Singh · Julian Michael · Felix Hill · Omer Levy · Samuel R. Bowman
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #74
Quaternion Recurrent Neural Networks
Titouan Parcollet · Mirco Ravanellu · Mohamed Morchid · Georges Linarès · Chiheb Trabelsi · Renato De Mori · Yoshua Bengio
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #76
Neural TTS Stylization with Adversarial and Collaborative Games
shuang ma · Daniel McDuff · Yale Song
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #77
DialogWAE: Multimodal Response Generation with Conditional Wasserstein Auto-Encoder
Xiaodong Gu · Kyunghyun Cho · Jung-Woo Ha · Sunghun Kim
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #78
Exemplar Guided Unsupervised Image-to-Image Translation with Semantic Consistency
Liqian Ma · Xu Jia · Stamatios Georgoulis · Tinne Tuytelaars · Luc Gool
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #79
Improving Sequence-to-Sequence Learning via Optimal Transport
Liqun Chen · Yizhe Zhang · Ruiyi Zhang · Chenyang Tao · Zhe Gan · Haichao Zhang · Bai Li · Dinghan Shen · Changyou Chen · Lawrence Carin
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #80
A Max-Affine Spline Perspective of Recurrent Neural Networks
Richard Baraniuk · Jack Wang · Randall Balestriero
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #81
No Training Required: Exploring Random Encoders for Sentence Classification
John Wieting · Douwe Kiela
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #82
Improving Differentiable Neural Computers Through Memory Masking, De-allocation, and Link Distribution Sharpness Control
Róbert Csordás · Jürgen Schmidhuber
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #83
TimbreTron: A WaveNet(CycleGAN(CQT(Audio))) Pipeline for Musical Timbre Transfer
Sicong(Sheldon) Huang · Qiyang Li · Cem Anil · Xuchan Bao · Sageev Oore · Roger Grosse
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #84
Learning to Screen for Fast Softmax Inference on Large Vocabulary Neural Networks
Patrick CHen · Si Si · Sanjiv Kumar · Yang Li · Cho-Jui Hsieh
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #85
Learning to Understand Goal Specifications by Modelling Reward
Felix Hill · Jan Leike · Edward Hughes · Arian Hosseini · Pushmeet Kohli · Edward Grefenstette · Dzmitry Bahdanau
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #86
BabyAI: A Platform to Study the Sample Efficiency of Grounded Language Learning
Maxime Chevalier-Boisvert · Dzmitry Bahdanau · Salem Lahlou · Lucas Willems · Chitwan Saharia · Thien H Nguyen · Yoshua Bengio
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #87
Learning to Adapt in Dynamic, Real-World Environments through Meta-Reinforcement Learning
Anusha Nagabandi · Ignasi Clavera · Simin Liu · Ronald Fearing · Pieter Abbeel · Sergey Levine · Chelsea Finn
Break
Thu May 9th 01:00 -- 02:30 PM @ on your own
Lunch - on your own
Invited Talk
Thu May 9th 02:30 -- 03:15 PM @ Great Hall AD
Learning (from) language in context
Noah Goodman
Oral
Thu May 9th 03:15 -- 03:30 PM @ Great Hall AD
Meta-Learning Update Rules for Unsupervised Representation Learning
Luke Metz · Niru Maheswaranathan · Brian Cheung · Jascha Sohl-Dickstein
Oral
Thu May 9th 03:30 -- 03:45 PM @ Great Hall AD
Temporal Difference Variational Auto-Encoder
Karol Gregor · George Papamakarios · Frederic Besse · Lars Buesing · Theophane Weber
Oral
Thu May 9th 03:45 -- 04:00 PM @ Great Hall AD
Transferring Knowledge across Learning Processes
Sebastian Flennerhag · Pablo Moreno · Neil D Lawrence · Andreas Damianou
Break
Thu May 9th 04:00 -- 04:30 PM @ Hall B-1
Coffee Break
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #1
Stable Opponent Shaping in Differentiable Games
Alistair Letcher · Jakob N Foerster · David Balduzzi · Tim Rocktaeschel · Shimon Whiteson
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #2
Lagging Inference Networks and Posterior Collapse in Variational Autoencoders
Junxian He · Daniel Spokoyny · Graham Neubig · Taylor Berg-Kirkpatrick
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #3
Preventing Posterior Collapse with delta-VAEs
Ali Razavi · Aaron van den Oord · Ben Poole · Oriol Vinyals
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #4
Spectral Inference Networks: Unifying Deep and Spectral Learning
David Pfau · Stig Petersen · Ashish Agarwal · David GT Barrett · Kimberly L Stachenfeld
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #5
Learning Programmatically Structured Representations with Perceptor Gradients
Svetlin Penkov · Subramanian Ramamoorthy
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #6
Variational Bayesian Phylogenetic Inference
Cheng Zhang · Frederick A Matsen
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #7
Analyzing Inverse Problems with Invertible Neural Networks
Lynton Ardizzone · Jakob Kruse · Carsten Rother · Ullrich Koethe
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #8
Learning Representations of Sets through Optimized Permutations
Yan Zhang · Jonathon Hare · Adam Prugel-Bennett
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #9
Stochastic Prediction of Multi-Agent Interactions from Partial Observations
Chen Sun · Per Karlsson · Jiajun Wu · Joshua B Tenenbaum · Kevin Murphy
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #10
Distribution-Interpolation Trade off in Generative Models
Damian Leśniak · Igor Sieradzki · Igor Podolak
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #11
Diagnosing and Enhancing VAE Models
Bin Dai · David Wipf
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #12
Generative Question Answering: Learning to Answer the Whole Question
Mike Lewis · Angela Fan
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #13
Interpolation-Prediction Networks for Irregularly Sampled Time Series
Satya Narayan Shukla · Benjamin M Marlin
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #14
FUNCTIONAL VARIATIONAL BAYESIAN NEURAL NETWORKS
Shengyang Sun · Guodong Zhang · Jiaxin Shi · Roger Grosse
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #15
ARM: Augment-REINFORCE-Merge Gradient for Stochastic Binary Networks
Mingzhang Yin · Mingyuan Zhou
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #16
Integer Networks for Data Compression with Latent-Variable Models
Johannes Ballé · Nick Johnston · David Minnen
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #17
Optimal Transport Maps For Distribution Preserving Operations on Latent Spaces of Generative Models
Eirikur Agustsson · Alexander Sage · Radu Timofte · Luc S.J Van Gool
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #18
MARGINALIZED AVERAGE ATTENTIONAL NETWORK FOR WEAKLY-SUPERVISED LEARNING
Yuan Yuan · YUEMING LYU · Xi SHEN · Ivor Wai-Hung Tsang · Dit-Yan Yeung
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #19
Deep, Skinny Neural Networks are not Universal Approximators
Jesse Johnson
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #20
Function Space Particle Optimization for Bayesian Neural Networks
Ziyu Wang · Tongzheng Ren · Jun Zhu · Bo Zhang
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #21
Measuring Compositionality in Representation Learning
Jacob Andreas
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #22
Variational Autoencoders with Jointly Optimized Latent Dependency Structure
Jiawei He · Yu Gong · Joe Marino · Greg Mori · Andreas Lehrmann
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #23
Learning Factorized Multimodal Representations
Yao Hung Tsai · Paul Pu Liang · Amir Ali Bagherzade · Louis-Philippe Morency · Ruslan Salakhutdinov
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #24
On the loss landscape of a class of deep neural networks with no bad local valleys
Quynh Nguyen · Mahesh Chandra Mukkamala · Matthias Hein
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #25
Attentive Neural Processes
Hyunjik Kim · Andriy Mnih · Jonathan Schwarz · Marta Garnelo · S. M. Ali Eslami · Dan Rosenbaum · Oriol Vinyals · Yee Whye Teh
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #26
ClariNet: Parallel Wave Generation in End-to-End Text-to-Speech
Wei Ping · Kainan Peng · Jitong Chen
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #27
Label super-resolution networks
Nikolay Malkin · Caleb Robinson · Le Hou · Rachel Soobitsky · Jacob Czawlytko · Dimitris Samaras · Joel Saltz · Lucas Joppa · Nebojsa Jojic
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #28
Learning from Positive and Unlabeled Data with a Selection Bias
Masahiro Kato · Takeshi Teshima · Junya Honda
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #29
Transferring Knowledge across Learning Processes
Sebastian Flennerhag · Pablo Moreno · Neil D Lawrence · Andreas Damianou
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #30
Deep learning generalizes because the parameter-function map is biased towards simple functions
Guillermo Valle-Perez · Chico Q. Camargo · Ard Louis
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #31
Temporal Difference Variational Auto-Encoder
Karol Gregor · George Papamakarios · Frederic Besse · Lars Buesing · Theophane Weber
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #32
Practical lossless compression with latent variables using bits back coding
James Townsend · Thomas Bird · David Barber
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #33
Unsupervised Control Through Non-Parametric Discriminative Rewards
David Warde-Farley · Tom Wiele · Tejas Kulkarni · Catalin Ionescu · Steven S Hansen · Volodymyr Mnih
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #34
Information Theoretic lower bounds on negative log likelihood
Luis Lastras
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #35
Unsupervised Domain Adaptation for Distance Metric Learning
Kihyuk Sohn · Wenling Shang · Xiang Yu · Manmohan Chandraker
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #36
Janossy Pooling: Learning Deep Permutation-Invariant Functions for Variable-Size Inputs
Ryan L Murphy · Balasubramaniam Srinivasan · Vinayak Rao · Bruno Ribeiro
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #37
Learning Neural PDE Solvers with Convergence Guarantees
Jun-Ting Hsieh · Shengjia Zhao · Stephan Eismann · Lucia Mirabella · Stefano Ermon
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #38
How Important is a Neuron
Kedar Dhamdhere · Mukund Sundararajan · Qiqi Yan
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #39
Learning Procedural Abstractions and Evaluating Discrete Latent Temporal Structure
Karan Goel · Emma Brunskill
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #40
Auxiliary Variational MCMC
Raza Habib · David Barber
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #41
Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology
Bastian A. Rieck · Matteo Togninalli · Christian Bock · Michael Moor · Max Horn · Thomas Gumbsch · Karsten Borgwardt
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #42
Learning-Based Frequency Estimation Algorithms
Chen-Yu Hsu · Piotr Indyk · Dina Katabi · Ali Vakilian
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #43
Generative predecessor models for sample-efficient imitation learning
Yannick Schroecker · Mel Vecerik · Jon Scholz
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #44
Efficient Augmentation via Data Subsampling
Michael Kuchnik · Virginia Smith
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #45
LEARNING FACTORIZED REPRESENTATIONS FOR OPEN-SET DOMAIN ADAPTATION
Mahsa Baktashmotlagh · Masoud Faraki · Tom Drummond · Mathieu Salzmann
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #46
Sliced Wasserstein Auto-Encoders
Soheil Kolouri · Phillip Pope · Charles Martin · Gustavo Rohde
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #47
Maximal Divergence Sequential Autoencoder for Binary Software Vulnerability Detection
Tue Le · Tuan Nguyen · Trung Le · Dinh Phung · Paul Montague · Olivier Vel · Lizhen Qu
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #48
The Deep Weight Prior
Andrei Atanov · Arsenii Ashukha · Kirill Struminsky · Dmitry P. Vetrov · Max Welling
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #49
Feature-Wise Bias Amplification
Klas Leino · Matt Fredrikson · Emily Black · Shayak Sen · Anupam Datta
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #50
Generating Liquid Simulations with Deformation-aware Neural Networks
Lukas Prantl · Boris Bonev · Nils Thuerey
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #51
Learning Grid Cells as Vector Representation of Self-Position Coupled with Matrix Representation of Self-Motion
Ruiqi Gao · Jianwen Xie · Song-Chun Zhu · Yingnian Wu
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #52
Toward Understanding the Impact of Staleness in Distributed Machine Learning
Wei Dai · Yi Zhou · Nanqing Dong · Hao Zhang · Eric Xing
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #53
Dimensionality Reduction for Representing the Knowledge of Probabilistic Models
Marc T Law · Jake Snell · Amir-massoud Farahmand · Raquel Urtasun · Richard Zemel
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #54
GamePad: A Learning Environment for Theorem Proving
Daniel Huang · Prafulla Dhariwal · Dawn Song · Ilya Sutskever
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #55
Active Learning with Partial Feedback
Peiyun Hu · Zachary Lipton · Anima Anandkumar · Deva Ramanan
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #56
On the Turing Completeness of Modern Neural Network Architectures
Jorge Pérez · Javier Marinković · Pablo Barceló
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #57
Learning a Meta-Solver for Syntax-Guided Program Synthesis
Xujie Si · Yuan Yang · Hanjun Dai · Mayur Naik · Le Song
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #58
DHER: Hindsight Experience Replay for Dynamic Goals
Meng Fang · Cheng Zhou · Bei Shi · Boqing Gong · Jia Xu · Tong Zhang
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #59
Spreading vectors for similarity search
Alexandre Sablayrolles · Matthijs Douze · Cordelia Schmid · Hervé Jégou
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #60
Feed-forward Propagation in Probabilistic Neural Networks with Categorical and Max Layers
Alexander (Oleksandr) Shekhovtsov · Boris Flach
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #61
Kernel Change-point Detection with Auxiliary Deep Generative Models
Wei-Cheng Chang · Chun-Liang Li · Yiming Yang · Barnabás Póczos
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #62
Do Deep Generative Models Know What They Don't Know?
Eric Nalisnick · Akihiro Matsukawa · Yee Whye Teh · Dilan Gorur · Balaji Lakshminarayanan
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #63
Unsupervised Learning of the Set of Local Maxima
Lior Wolf · Sagie Benaim · Tomer Galanti
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #64
Modeling Uncertainty with Hedged Instance Embeddings
Seong Joon Oh · Andrew Gallagher · Kevin Murphy · Florian Schroff · Jiyan Pan · Joseph Roth
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #65
Bias-Reduced Uncertainty Estimation for Deep Neural Classifiers
Yonatan Geifman · Guy Uziel · Ran El-Yaniv
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #66
Learning Particle Dynamics for Manipulating Rigid Bodies, Deformable Objects, and Fluids
Yunzhu Li · Jiajun Wu · Russ Tedrake · Joshua B Tenenbaum · Antonio Torralba
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #67
Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives
George Tucker · Dieterich Lawson · Shixiang Gu · Chris J Maddison
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #68
Attention, Learn to Solve Routing Problems!
Wouter Kool · Herke van Hoof · Max Welling
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #69
Amortized Bayesian Meta-Learning
Sachin Ravi · Alex Beatson
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #70
Meta-Learning Update Rules for Unsupervised Representation Learning
Luke Metz · Niru Maheswaranathan · Brian Cheung · Jascha Sohl-Dickstein
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #71
MAE: Mutual Posterior-Divergence Regularization for Variational AutoEncoders
Xuezhe Ma · Chunting Zhou · Eduard Hovy
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #72
Variance Networks: When Expectation Does Not Meet Your Expectations
Kirill Neklyudov · Dmitry Molchanov · Arsenii Ashukha · Dmitry P. Vetrov
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #73
Wasserstein Barycenter Model Ensembling
Pierre Dognin · Igor Melnyk · Youssef Mroueh · Jarret Ross · Cicero Nogueira dos Santos · Tom Sercu
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #74
Variational Autoencoder with Arbitrary Conditioning
Oleg Ivanov · Mikhail Figurnov · Dmitry P. Vetrov
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #75
Beyond Greedy Ranking: Slate Optimization via List-CVAE
Ray Jiang · Sven Gowal · Yuqiu Qian · Timothy A Mann · Danilo J Rezende
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #76
Bayesian Policy Optimization for Model Uncertainty
Gilwoo Lee · Brian Hou · Aditya Mandalika · Jeongseok Lee · Sanjiban Choudhury · Siddhartha Srinivasa
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #77
Efficiently testing local optimality and escaping saddles for ReLU networks
Chulhee Yun · Suvrit Sra · Ali Jadbabaie
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #78
Accumulation Bit-Width Scaling For Ultra-Low Precision Training Of Deep Networks
Charbel Sakr · Naigang Wang · Chia-Yu Chen · Jungwook Choi · Ankur Agrawal · Naresh Shanbhag · Kailash Gopalakrishnan
Break
Thu May 9th 06:30 -- 08:30 PM @ Great Hall Pre-Function, Hall B-1
Closing Reception