ICLR 2019

502 papers

ALISTA: Analytic Weights Are As Good As Learned Weights in LISTA

Jialin Liu, Xiaohan Chen, Zhangyang Wang, Wotao Yin

Efficient Augmentation via Data Subsampling

Michael Kuchnik, Virginia Smith

Value Propagation Networks

Nantas Nardelli, Gabriel Synnaeve, Zeming Lin, Pushmeet Kohli, Philip H. S. Torr

Deep Online Learning Via Meta-Learning: Continual Adaptation for Model-Based RL

Anusha Nagabandi, Chelsea Finn, Sergey Levine

Preventing Posterior Collapse with delta-VAEs

Ali Razavi, Aaron van den Oord, Ben Poole, Oriol Vinyals

Learning Grid Cells as Vector Representation of Self-Position Coupled with Matrix Representation of Self-Motion

Ruiqi Gao, Jianwen Xie, Song-chun Zhu, Ying Nian Wu

Plan Online, Learn Offline: Efficient Learning and Exploration via Model-Based Control

Kendall Lowrey, Aravind Rajeswaran, Sham Kakade, Emanuel Todorov, Igor Mordatch

GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding

Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy

An Empirical Study of Example Forgetting during Deep Neural Network Learning

Mariya Toneva*, Alessandro Sordoni*, Remi Tachet des Combes*, Adam Trischler, Yoshua Bengio

Optimal Control Via Neural Networks: A Convex Approach

Yize Chen, Yuanyuan Shi, Baosen Zhang

Adaptive Input Representations for Neural Language Modeling

Alexei Baevski, Michael Auli

Systematic Generalization: What Is Required and Can It Be Learned?

Dzmitry Bahdanau*, Shikhar Murty*, Michael Noukhovitch, Thien Huu Nguyen, Harm de Vries

Automatically Composing Representation Transformations as a Means for Generalization

Michael Chang, Abhishek Gupta, Sergey Levine, Thomas L. Griffiths

Modeling Uncertainty with Hedged Instance Embeddings

Seong Joon Oh, Kevin P. Murphy, Jiyan Pan, Joseph Roth, Florian Schroff

Learning to Navigate the Web

Izzeddin Gur, Ulrich Rueckert, Aleksandra Faust, Dilek Hakkani-Tur

RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space

Zhiqing Sun, Zhi-Hong Deng, Jian-Yun Nie, Jian Tang

STCN: Stochastic Temporal Convolutional Networks

Emre Aksan, Otmar Hilliges

A Closer Look at Few-shot Classification

Wei-Yu Chen, Yen-Cheng Liu, Zsolt Kira, Yu-Chiang Frank Wang, Jia-Bin Huang

A Mean Field Theory of Batch Normalization

Greg Yang, Jeffrey Pennington, Vinay Rao, Jascha Sohl-dickstein, Samuel S. Schoenholz

TimbreTron: A WaveNet(CycleGAN(CQT(Audio))) Pipeline for Musical Timbre Transfer

Sicong Huang, Qiyang Li, Cem Anil, Xuchan Bao, Sageev Oore

GAN Dissection: Visualizing and Understanding Generative Adversarial Networks

David Bau, Jun-Yan Zhu, Hendrik Strobelt, Bolei Zhou, Joshua B. Tenenbaum

Learning to Learn with Conditional Class Dependencies

Xiang Jiang, Mohammad Havaei, Farshid Varno, Gabriel Chartrand, Nicolas Chapados

AD-VAT: An Asymmetric Dueling mechanism for learning Visual Active Tracking

Fangwei Zhong, peng sun, Wenhan Luo, Tingyun Yan, Yizhou Wang

Feature-Wise Bias Amplification

Klas Leino, Emily Black, Matt Fredrikson, Shayak Sen, Anupam Datta

Top-Down Neural Model For Formulae

Karel Chvalovský

A Max-Affine Spline Perspective of Recurrent Neural Networks

Zichao Wang, Randall Balestriero, Richard Baraniuk

Competitive experience replay

Hao Liu, Alexander Trott, Richard Socher, Caiming Xiong

Rigorous Agent Evaluation: An Adversarial Approach to Uncover Catastrophic Failures

Jonathan Uesato*, Ananya Kumar*, Csaba Szepesvari*, Tom Erez, Avraham Ruderman

Don't let your Discriminator be fooled

Brady Zhou, Philipp Krähenbühl

Efficiently testing local optimality and escaping saddles for ReLU networks

Chulhee Yun, Suvrit Sra, Ali Jadbabaie

Diagnosing and Enhancing VAE Models

Bin Dai, David Wipf

Tree-Structured Recurrent Switching Linear Dynamical Systems for Multi-Scale Modeling

Josue Nassar, Scott Linderman, Monica Bugallo, Il Memming Park

Algorithmic Framework for Model-based Deep Reinforcement Learning with Theoretical Guarantees

Yuping Luo, Huazhe Xu, Yuanzhi Li, Yuandong Tian, Trevor Darrell

Differentiable Perturb-and-Parse: Semi-Supervised Parsing with a Structured Variational Autoencoder

Caio Corro, Ivan Titov

Two-Timescale Networks for Nonlinear Value Function Approximation

Wesley Chung, Somjit Nath, Ajin Joseph, Martha White

Boosting Robustness Certification of Neural Networks

Gagandeep Singh, Timon Gehr, Markus Püschel, Martin Vechev

Spherical CNNs on Unstructured Grids

Chiyu Max Jiang, Jingwei Huang, Karthik Kashinath, Prabhat, Philip Marcus

G-SGD: Optimizing ReLU Neural Networks in its Positively Scale-Invariant Space

Qi Meng, Shuxin Zheng, Huishuai Zhang, Wei Chen, Qiwei Ye

Beyond Greedy Ranking: Slate Optimization via List-CVAE

Ray Jiang, Sven Gowal, Yuqiu Qian, Timothy Mann, Danilo J. Rezende

Toward Understanding the Impact of Staleness in Distributed Machine Learning

Wei Dai, Yi Zhou, Nanqing Dong, Hao Zhang, Eric Xing

GANSynth: Adversarial Neural Audio Synthesis

Jesse Engel, Kumar Krishna Agrawal, Shuo Chen, Ishaan Gulrajani, Chris Donahue

Characterizing Audio Adversarial Examples Using Temporal Dependency

Zhuolin Yang, Bo Li, Pin-Yu Chen, Dawn Song

DISTRIBUTIONAL CONCAVITY REGULARIZATION FOR GANS

Shoichiro Yamaguchi, Masanori Koyama

Efficient Multi-Objective Neural Architecture Search via Lamarckian Evolution

Thomas Elsken, Jan Hendrik Metzen, Frank Hutter

On the Sensitivity of Adversarial Robustness to Input Data Distributions

Gavin Weiguang Ding, Kry Yik Chau Lui, Xiaomeng Jin, Luyu Wang, Ruitong Huang

Active Learning with Partial Feedback

Peiyun Hu, Zachary C. Lipton, Anima Anandkumar, Deva Ramanan

Guiding Policies with Language via Meta-Learning

John D. Co-Reyes, Abhishek Gupta, Suvansh Sanjeev, Nick Altieri, Jacob Andreas

Learnable Embedding Space for Efficient Neural Architecture Compression

Shengcao Cao, Xiaofang Wang, Kris M. Kitani

MisGAN: Learning from Incomplete Data with Generative Adversarial Networks

Steven Cheng-Xian Li, Bo Jiang, Benjamin Marlin

K for the Price of 1: Parameter-efficient Multi-task and Transfer Learning

Pramod Kaushik Mudrakarta, Mark Sandler, Andrey Zhmoginov, Andrew Howard

Do Deep Generative Models Know What They Don't Know?

Eric Nalisnick, Akihiro Matsukawa, Yee Whye Teh, Dilan Gorur, Balaji Lakshminarayanan

RelGAN: Relational Generative Adversarial Networks for Text Generation

Weili Nie, Nina Narodytska, Ankit Patel

NOODL: Provable Online Dictionary Learning and Sparse Coding

Sirisha Rambhatla, Xingguo Li, Jarvis Haupt

Posterior Attention Models for Sequence to Sequence Learning

Shiv Shankar, Sunita Sarawagi

Reasoning About Physical Interactions with Object-Oriented Prediction and Planning

Michael Janner, Sergey Levine, William T. Freeman, Joshua B. Tenenbaum, Chelsea Finn

Universal Stagewise Learning for Non-Convex Problems with Convergence on Averaged Solutions

Zaiyi Chen, Zhuoning Yuan, Jinfeng Yi, Bowen Zhou, Enhong Chen

SPIGAN: Privileged Adversarial Learning from Simulation

Kuan-Hui Lee, German Ros, Jie Li, Adrien Gaidon

Learning sparse relational transition models

Victoria Xia, Zi Wang, Kelsey Allen, Tom Silver, Leslie Pack Kaelbling

Multi-Agent Dual Learning

Yiren Wang, Yingce Xia, Tianyu He, Fei Tian, Tao Qin

Multiple-Attribute Text Rewriting

Guillaume Lample, Sandeep Subramanian, Eric Smith, Ludovic DENOYER, Marc'aurelio Ranzato

A Variational Inequality Perspective on Generative Adversarial Networks

Gauthier Gidel, Hugo Berard, Gaëtan Vignoud, Pascal Vincent, Simon Lacoste-Julien

Combinatorial Attacks on Binarized Neural Networks

Elias B Khalil, Amrita Gupta, Bistra Dilkina

Cost-Sensitive Robustness against Adversarial Examples

Xiao Zhang, David Evans

Learning to Design RNA

Frederic Runge, Danny Stoll, Stefan Falkner, Frank Hutter

Learning Procedural Abstractions and Evaluating Discrete Latent Temporal Structure

Karan Goel, Emma Brunskill

Disjoint Mapping Network for Cross-modal Matching of Voices and Faces

Yandong Wen, Mahmoud Al Ismail, Weiyang Liu, Bhiksha Raj, Rita Singh

Representing Formal Languages: A Comparison Between Finite Automata and Recurrent Neural Networks

Joshua J. Michalenko, Ameesh Shah, Abhinav Verma, Richard G. Baraniuk, Swarat Chaudhuri

Learning Particle Dynamics for Manipulating Rigid Bodies, Deformable Objects, and Fluids

Yunzhu Li, Jiajun Wu, Russ Tedrake, Joshua B. Tenenbaum, Antonio Torralba

Selfless Sequential Learning

Rahaf Aljundi, Marcus Rohrbach, Tinne Tuytelaars

Neural Graph Evolution: Towards Efficient Automatic Robot Design

Tingwu Wang, Yuhao Zhou, Sanja Fidler, Jimmy Ba

Contingency-Aware Exploration in Reinforcement Learning

Jongwook Choi, Yijie Guo, Marcin Moczulski, Junhyuk Oh, Neal Wu

Interpolation-Prediction Networks for Irregularly Sampled Time Series

Satya Narayan Shukla, Benjamin Marlin

Learning to Screen for Fast Softmax Inference on Large Vocabulary Neural Networks

Patrick Chen, Si Si, Sanjiv Kumar, Yang Li, Cho-jui Hsieh

Model-Predictive Policy Learning with Uncertainty Regularization for Driving in Dense Traffic

Mikael Henaff, Alfredo Canziani, Yann LeCun

Modeling the Long Term Future in Model-Based Reinforcement Learning

Nan Rosemary Ke, Amanpreet Singh, Ahmed Touati, Anirudh Goyal, Yoshua Bengio

Music Transformer: Generating Music with Long-Term Structure

Cheng-Zhi Anna Huang, Ashish Vaswani, Jakob Uszkoreit, Ian Simon, Curtis Hawthorne

Learning to Infer and Execute 3D Shape Programs

Yonglong Tian, Andrew Luo, Xingyuan Sun, Kevin Ellis, William T. Freeman

A Generative Model For Electron Paths

John Bradshaw, Matt J. Kusner, Brooks Paige, Marwin H. S. Segler, José Miguel Hernández-Lobato

ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware

Han Cai, Ligeng Zhu, Song Han

Revealing interpretable object representations from human behavior

Charles Y. Zheng, Francisco Pereira, Chris I. Baker, Martin N. Hebart

Composing Complex Skills by Learning Transition Policies

Youngwoon Lee*, Shao-Hua Sun*, Sriram Somasundaram, Edward S. Hu, Joseph J. Lim

Energy-Constrained Compression for Deep Neural Networks via Weighted Sparse Projection and Layer Input Masking

Haichuan Yang, Yuhao Zhu, Ji Liu

Stochastic Optimization of Sorting Networks via Continuous Relaxations

Aditya Grover, Eric Wang, Aaron Zweig, Stefano Ermon

Learning a Meta-Solver for Syntax-Guided Program Synthesis

Xujie Si, Yuan Yang, Hanjun Dai, Mayur Naik, Le Song

Capsule Graph Neural Network

Zhang Xinyi, Lihui Chen

Multi-step Retriever-Reader Interaction for Scalable Open-domain Question Answering

Rajarshi Das, Shehzaad Dhuliawala, Manzil Zaheer, Andrew McCallum

Label super-resolution networks

Kolya Malkin, Caleb Robinson, Le Hou, Rachel Soobitsky, Jacob Czawlytko

DyRep: Learning Representations over Dynamic Graphs

Rakshit Trivedi, Mehrdad Farajtabar, Prasenjeet Biswal, Hongyuan Zha

Stochastic Prediction of Multi-Agent Interactions from Partial Observations

Chen Sun, Per Karlsson, Jiajun Wu, Joshua B Tenenbaum, Kevin Murphy

Synthetic Datasets for Neural Program Synthesis

Richard Shin, Neel Kant, Kavi Gupta, Chris Bender, Brandon Trabucco

There Are Many Consistent Explanations of Unlabeled Data: Why You Should Average

Ben Athiwaratkun, Marc Finzi, Pavel Izmailov, Andrew Gordon Wilson

Towards GAN Benchmarks Which Require Generalization

Ishaan Gulrajani, Colin Raffel, Luke Metz

Eidetic 3D LSTM: A Model for Video Prediction and Beyond

Yunbo Wang, Lu Jiang, Ming-Hsuan Yang, Li-jia Li, Mingsheng Long

Poincare Glove: Hyperbolic Word Embeddings

Alexandru Tifrea*, Gary Becigneul*, Octavian-Eugen Ganea*

On the Universal Approximability and Complexity Bounds of Quantized ReLU Neural Networks

Yukun Ding, Jinglan Liu, Jinjun Xiong, Yiyu Shi

Neural TTS Stylization with Adversarial and Collaborative Games

Shuang Ma, Daniel McDuff, Yale Song

Rethinking the Value of Network Pruning

Zhuang Liu, Mingjie Sun, Tinghui Zhou, Gao Huang, Trevor Darrell

Global-to-local Memory Pointer Networks for Task-Oriented Dialogue

Chien-Sheng Wu, Richard Socher, Caiming Xiong

Learning to Learn without Forgetting by Maximizing Transfer and Minimizing Interference

Matthew Riemer, Ignacio Cases, Robert Ajemian, Miao Liu, Irina Rish

The Limitations of Adversarial Training and the Blind-Spot Attack

Huan Zhang*, Hongge Chen*, Zhao Song, Duane Boning, Inderjit S. Dhillon