Papers
Invariant Representations without Adversarial Training
Daniel Moyer, Shuyang Gao, Rob Brekelmans et al.
Processing of missing data by neural networks
Marek Śmieja, Łukasz Struski, Jacek Tabor et al.
Contextual Pricing for Lipschitz Buyers
Jieming Mao, Renato Leme, Jon Schneider
Global Non-convex Optimization with Discretized Diffusions
Murat A Erdogdu, Lester Mackey, Ohad Shamir
The Cluster Description Problem - Complexity Results, Formulations and Approximations
Ian Davidson, Antoine Gourru, S Ravi
Differential Properties of Sinkhorn Approximation for Learning with Wasserstein Distance
Giulia Luise, Alessandro Rudi, Massimiliano Pontil et al.
Hybrid Macro/Micro Level Backpropagation for Training Deep Spiking Neural Networks
Yingyezhe Jin, Wenrui Zhang, Peng Li
Scaling the Poisson GLM to massive neural datasets through polynomial approximations
David Zoltowski, Jonathan W Pillow
Multiple-Step Greedy Policies in Approximate and Online Reinforcement Learning
Yonathan Efroni, Gal Dalal, Bruno Scherrer et al.
An Off-policy Policy Gradient Theorem Using Emphatic Weightings
Ehsan Imani, Eric Graves, Martha White
Graph Oracle Models, Lower Bounds, and Gaps for Parallel Stochastic Optimization
Blake E Woodworth, Jialei Wang, Adam Smith et al.
Predictive Uncertainty Estimation via Prior Networks
Andrey Malinin, Mark Gales
Towards Robust Interpretability with Self-Explaining Neural Networks
David Alvarez Melis, Tommi Jaakkola
Inexact trust-region algorithms on Riemannian manifolds
Hiroyuki Kasai, Bamdev Mishra
Approximation algorithms for stochastic clustering
David Harris, Shi Li, Aravind Srinivasan et al.
The challenge of realistic music generation: modelling raw audio at scale
Sander Dieleman, Aaron van den Oord, Karen Simonyan
Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models
Kurtland Chua, Roberto Calandra, Rowan McAllister et al.
Non-Adversarial Mapping with VAEs
Yedid Hoshen
Early Stopping for Nonparametric Testing
Meimei Liu, Guang Cheng
Scalable Laplacian K-modes
Imtiaz Ziko, Eric Granger, Ismail Ben Ayed
Semi-crowdsourced Clustering with Deep Generative Models
Yucen Luo, TIAN TIAN, Jiaxin Shi et al.
The Description Length of Deep Learning models
Léonard Blier, Yann Ollivier
Privacy Amplification by Subsampling: Tight Analyses via Couplings and Divergences
Borja Balle, Gilles Barthe, Marco Gaboardi
Mesh-TensorFlow: Deep Learning for Supercomputers
Noam Shazeer, Youlong Cheng, Niki Parmar et al.