Papers
Leveraging Grammar and Reinforcement Learning for Neural Program Synthesis
Rudy Bunel, Matthew Hausknecht, Jacob Devlin et al.
Deep Learning as a Mixed Convex-Combinatorial Optimization Problem
Abram L. Friesen, Pedro Domingos
A PAC-Bayesian Approach to Spectrally-Normalized Margin Bounds for Neural Networks
Behnam Neyshabur, Srinadh Bhojanapalli, Nathan Srebro
A Scalable Laplace Approximation for Neural Networks
Hippolyt Ritter, Aleksandar Botev, David Barber
Understanding Short-Horizon Bias in Stochastic Meta-Optimization
Yuhuai Wu, Mengye Ren, Renjie Liao et al.
Learning From Noisy Singly-labeled Data
Ashish Khetan, Zachary C. Lipton, Animashree Anandkumar
Learning One-hidden-layer Neural Networks with Landscape Design
Rong Ge, Jason D. Lee, Tengyu Ma
Do GANs learn the distribution? Some Theory and Empirics
Sanjeev Arora, Andrej Risteski, Yi Zhang
Towards Synthesizing Complex Programs From Input-Output Examples
Xinyun Chen, Chang Liu, Dawn Song
The Reactor: A fast and sample-efficient Actor-Critic agent for Reinforcement Learning
Audrunas Gruslys, Will Dabney, Mohammad Gheshlaghi Azar et al.
On the Discrimination-Generalization Tradeoff in GANs
Pengchuan Zhang, Qiang Liu, Dengyong Zhou et al.
WRPN: Wide Reduced-Precision Networks
Asit Mishra, Eriko Nurvitadhi, Jeffrey J Cook et al.
Learning how to explain neural networks: PatternNet and PatternAttribution
Pieter-Jan Kindermans, Kristof T. Schütt, Maximilian Alber et al.
The Kanerva Machine: A Generative Distributed Memory
Yan Wu, Greg Wayne, Alex Graves et al.
Attacking Binarized Neural Networks
Angus Galloway, Graham W. Taylor, Medhat Moussa
Emergent Communication in a Multi-Modal, Multi-Step Referential Game
Katrina Evtimova, Andrew Drozdov, Douwe Kiela et al.
Monotonic Chunkwise Attention
Chung-Cheng Chiu*, Colin Raffel*
Learning Awareness Models
Brandon Amos, Laurent Dinh, Serkan Cabi et al.
Latent Space Oddity: on the Curvature of Deep Generative Models
Georgios Arvanitidis, Lars Kai Hansen, Søren Hauberg
Training GANs with Optimism
Constantinos Daskalakis, Andrew Ilyas, Vasilis Syrgkanis et al.
Implicit Causal Models for Genome-wide Association Studies
Dustin Tran, David M. Blei
Adaptive Dropout with Rademacher Complexity Regularization
Ke Zhai, Huan Wang
Neural Language Modeling by Jointly Learning Syntax and Lexicon
Yikang Shen, Zhouhan Lin, Chin-wei Huang et al.
Leave no Trace: Learning to Reset for Safe and Autonomous Reinforcement Learning
Benjamin Eysenbach, Shixiang Gu, Julian Ibarz et al.
NerveNet: Learning Structured Policy with Graph Neural Networks
Tingwu Wang, Renjie Liao, Jimmy Ba et al.