Papers
Unsupervised Machine Translation Using Monolingual Corpora Only
Guillaume Lample, Alexis Conneau, Ludovic Denoyer et al.
Towards better understanding of gradient-based attribution methods for Deep Neural Networks
Marco Ancona, Enea Ceolini, Cengiz Öztireli et al.
Beyond Shared Hierarchies: Deep Multitask Learning through Soft Layer Ordering
Elliot Meyerson, Risto Miikkulainen
Simulated+Unsupervised Learning With Adaptive Data Generation and Bidirectional Mappings
Kangwook Lee, Hoon Kim, Changho Suh
SEARNN: Training RNNs with global-local losses
Rémi Leblond, Jean-Baptiste Alayrac, Anton Osokin et al.
Stabilizing Adversarial Nets with Prediction Methods
Abhay Yadav, Sohil Shah, Zheng Xu et al.
Large Scale Optimal Transport and Mapping Estimation
Vivien Seguy, Bharath Bhushan Damodaran, Remi Flamary et al.
Generating Natural Adversarial Examples
Zhengli Zhao, Dheeru Dua, Sameer Singh
Consequentialist conditional cooperation in social dilemmas with imperfect information
Alexander Peysakhovich, Adam Lerer
Can recurrent neural networks warp time?
Corentin Tallec, Yann Ollivier
Dynamic Neural Program Embeddings for Program Repair
Ke Wang, Rishabh Singh, Zhendong Su
Skip RNN: Learning to Skip State Updates in Recurrent Neural Networks
Víctor Campos, Brendan Jou, Xavier Giró-i-Nieto et al.
Multi-Mention Learning for Reading Comprehension with Neural Cascades
Swabha Swayamdipta, Ankur P. Parikh, Tom Kwiatkowski
Many Paths to Equilibrium: GANs Do Not Need to Decrease a Divergence At Every Step
William Fedus*, Mihaela Rosca*, Balaji Lakshminarayanan et al.
A Compressed Sensing View of Unsupervised Text Embeddings, Bag-of-n-Grams, and LSTMs
Sanjeev Arora, Mikhail Khodak, Nikunj Saunshi et al.
Deep Active Learning for Named Entity Recognition
Yanyao Shen, Hyokun Yun, Zachary C. Lipton et al.
Variational image compression with a scale hyperprior
Johannes Ballé, David Minnen, Saurabh Singh et al.
Hierarchical Subtask Discovery with Non-Negative Matrix Factorization
Adam C. Earle, Andrew M. Saxe, Benjamin Rosman
Generalizing Across Domains via Cross-Gradient Training
Shiv Shankar*, Vihari Piratla*, Soumen Chakrabarti et al.
Compositional Attention Networks for Machine Reasoning
Drew A. Hudson, Christopher D. Manning
Parameter Space Noise for Exploration
Matthias Plappert, Rein Houthooft, Prafulla Dhariwal et al.
Zero-Shot Visual Imitation
Deepak Pathak, Parsa Mahmoudieh, Guanghao Luo et al.
A DIRT-T Approach to Unsupervised Domain Adaptation
Rui Shu, Hung Bui, Hirokazu Narui et al.
Empirical Risk Landscape Analysis for Understanding Deep Neural Networks
Pan Zhou, Jiashi Feng
Learning Intrinsic Sparse Structures within Long Short-Term Memory
Wei Wen, Yuxiong He, Samyam Rajbhandari et al.