Papers
Why is Posterior Sampling Better than Optimism for Reinforcement Learning?
Ian Osband, Benjamin Van Roy
Algebraic Variety Models for High-Rank Matrix Completion
Greg Ongie, Rebecca Willett, Robert D. Nowak et al.
Deep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observability
Shayegan Omidshafiei, Jason Pazis, Christopher Amato et al.
The Statistical Recurrent Unit
Junier B. Oliva, Barnabás Póczos, Jeff Schneider
Zero-Shot Task Generalization with Multi-Task Deep Reinforcement Learning
Junhyuk Oh, Satinder Singh, Honglak Lee et al.
Nyström Method with Kernel K-means++ Samples as Landmarks
Dino Oglic, Thomas Gärtner
Conditional Image Synthesis with Auxiliary Classifier GANs
Augustus Odena, Christopher Olah, Jonathon Shlens
Multichannel End-to-end Speech Recognition
Tsubasa Ochiai, Shinji Watanabe, Takaaki Hori et al.
Composing Tree Graphical Models with Persistent Homology Features for Clustering Mixed-Type Data
Xiuyan Ni, Novi Quadrianto, Yusu Wang et al.
SARAH: A Novel Method for Machine Learning Problems Using Stochastic Recursive Gradient
Lam M. Nguyen, Jie Liu, Katya Scheinberg et al.
The Loss Surface of Deep and Wide Neural Networks
Quynh Nguyen, Matthias Hein
Post-Inference Prior Swapping
Willie Neiswanger, Eric Xing
Delta Networks for Optimized Recurrent Network Computation
Daniel Neil, Jun Haeng Lee, Tobi Delbruck et al.
Adaptive Sampling Probabilities for Non-Smooth Optimization
Hongseok Namkoong, Aman Sinha, Steve Yadlowsky et al.
Understanding the Representation and Computation of Multilayer Perceptrons: A Case Study in Speech Recognition
Tasha Nagamine, Nima Mesgarani
Meta Networks
Tsendsuren Munkhdalai, Hong Yu
Variants of RMSProp and Adagrad with Logarithmic Regret Bounds
Mahesh Chandra Mukkamala, Matthias Hein
Sequence to Better Sequence: Continuous Revision of Combinatorial Structures
Jonas Mueller, David Gifford, Tommi Jaakkola
McGan: Mean and Covariance Feature Matching GAN
Youssef Mroueh, Tom Sercu, Vaibhava Goel
Coupling Distributed and Symbolic Execution for Natural Language Queries
Lili Mou, Zhengdong Lu, Hang Li et al.
Regularising Non-linear Models Using Feature Side-information
Amina Mollaysa, Pablo Strasser, Alexandros Kalousis
Variational Dropout Sparsifies Deep Neural Networks
Dmitry Molchanov, Arsenii Ashukha, Dmitry Vetrov
Active Learning for Top-K Rank Aggregation from Noisy Comparisons
Soheil Mohajer, Changho Suh, Adel Elmahdy
Differentially Private Submodular Maximization: Data Summarization in Disguise
Marko Mitrovic, Mark Bun, Andreas Krause et al.
Improving Gibbs Sampler Scan Quality with DoGS
Ioannis Mitliagkas, Lester Mackey