ICLR 2018

337 papers

Universal Agent for Disentangling Environments and Tasks

Jiayuan Mao, Honghua Dong, Joseph J. Lim

Large scale distributed neural network training through online distillation

Rohan Anil, Gabriel Pereyra, Alexandre Passos, Robert Ormandi, George E. Dahl

Intrinsic Motivation and Automatic Curricula via Asymmetric Self-Play

Sainbayar Sukhbaatar, Zeming Lin, Ilya Kostrikov, Gabriel Synnaeve, arthur szlam

Rethinking the Smaller-Norm-Less-Informative Assumption in Channel Pruning of Convolution Layers

Jianbo Ye, Xin Lu, Zhe Lin, James Z. Wang

Adaptive Quantization of Neural Networks

Soroosh Khoram, Jing Li

Semantically Decomposing the Latent Spaces of Generative Adversarial Networks

Chris Donahue, Zachary C. Lipton, Akshay Balsubramani, Julian McAuley

Interpretable Counting for Visual Question Answering

Alexander Trott, Caiming Xiong, Richard Socher

Viterbi-based Pruning for Sparse Matrix with Fixed and High Index Compression Ratio

Dongsoo Lee, Daehyun Ahn, Taesu Kim, Pierce I. Chuang, Jae-Joon Kim

Compressing Word Embeddings via Deep Compositional Code Learning

Raphael Shu, Hideki Nakayama

Deep Complex Networks

Chiheb Trabelsi, Olexa Bilaniuk, Ying Zhang, Dmitriy Serdyuk, Sandeep Subramanian

Combining Symbolic Expressions and Black-box Function Evaluations in Neural Programs

Forough Arabshahi, Sameer Singh, Animashree Anandkumar

On the importance of single directions for generalization

Ari S. Morcos, David G.T. Barrett, Neil C. Rabinowitz, Matthew Botvinick

An efficient framework for learning sentence representations

Lajanugen Logeswaran, Honglak Lee

Stochastic Variational Video Prediction

Mohammad Babaeizadeh, Chelsea Finn, Dumitru Erhan, Roy H. Campbell, Sergey Levine

Deep contextualized word representations

Matthew E Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark

Meta-Learning for Semi-Supervised Few-Shot Classification

Mengye Ren, Eleni Triantafillou, Sachin Ravi, Jake Snell, Kevin Swersky

Learning Sparse Latent Representations with the Deep Copula Information Bottleneck

Aleksander Wieczorek*, Mario Wieser*, Damian Murezzan, Volker Roth

Stochastic Activation Pruning for Robust Adversarial Defense

Guneet S. Dhillon, Kamyar Azizzadenesheli, Zachary C. Lipton, Jeremy D. Bernstein, Jean Kossaifi

Trust-PCL: An Off-Policy Trust Region Method for Continuous Control

Ofir Nachum, Mohammad Norouzi, Kelvin Xu, Dale Schuurmans

PixelNN: Example-based Image Synthesis

Aayush Bansal, Yaser Sheikh, Deva Ramanan

Minimal-Entropy Correlation Alignment for Unsupervised Deep Domain Adaptation

Pietro Morerio, Jacopo Cavazza, Vittorio Murino

Smooth Loss Functions for Deep Top-k Classification

Leonard Berrada, Andrew Zisserman, M. Pawan Kumar

Learning to Count Objects in Natural Images for Visual Question Answering

Yan Zhang, Jonathon Hare, Adam Prugel-Bennett

Syntax-Directed Variational Autoencoder for Structured Data

Hanjun Dai, Yingtao Tian, Bo Dai, Steven Skiena, Le Song

Spherical CNNs

Taco S. Cohen, Mario Geiger, Jonas Köhler, Max Welling

Online Learning Rate Adaptation with Hypergradient Descent

Atilim Gunes Baydin, Robert Cornish, David Martinez Rubio, Mark Schmidt, Frank Wood

The Implicit Bias of Gradient Descent on Separable Data

Daniel Soudry, Elad Hoffer, Mor Shpigel Nacson, Nathan Srebro

Maximum a Posteriori Policy Optimisation

Abbas Abdolmaleki, Jost Tobias Springenberg, Yuval Tassa, Rémi Munos, Nicolas Heess

Meta-Learning and Universality: Deep Representations and Gradient Descent can Approximate any Learning Algorithm

Chelsea Finn, Sergey Levine

Critical Points of Linear Neural Networks: Analytical Forms and Landscape Properties

Yi Zhou, Yingbin Liang

Word translation without parallel data

Guillaume Lample, Alexis CONNEAU, Marc'aurelio Ranzato, Ludovic DENOYER, Herve Jegou

Unsupervised Learning of Goal Spaces for Intrinsically Motivated Goal Exploration

Alexandre Pere, Sébastien Forestier, Olivier Sigaud, Pierre-yves Oudeyer

Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models

Pouya Samangouei, Maya Kabkab, Rama Chellappa

WHAI: Weibull Hybrid Autoencoding Inference for Deep Topic Modeling

Hao Zhang, Bo Chen, Dandan Guo, Mingyuan Zhou

Bi-Directional Block Self-Attention for Fast and Memory-Efficient Sequence Modeling

Tao Shen, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang

Identifying Analogies Across Domains

Yedid Hoshen, Lior Wolf

Predicting Floor-Level for 911 Calls with Neural Networks and Smartphone Sensor Data

William Falcon, Henning Schulzrinne