Papers
Gradient descent GAN optimization is locally stable
Vaishnavh Nagarajan, J. Zico Kolter
Positive-Unlabeled Learning with Non-Negative Risk Estimator
Ryuichi Kiryo, Gang Niu, Marthinus C du Plessis et al.
Thy Friend is My Friend: Iterative Collaborative Filtering for Sparse Matrix Estimation
Christian Borgs, Jennifer Chayes, Christina E. Lee et al.
Dual-Agent GANs for Photorealistic and Identity Preserving Profile Face Synthesis
Jian Zhao, Lin Xiong, Panasonic Karlekar Jayashree et al.
Training Deep Networks without Learning Rates Through Coin Betting
Francesco Orabona, Tatiana Tommasi
Stabilizing Training of Generative Adversarial Networks through Regularization
Kevin Roth, Aurelien Lucchi, Sebastian Nowozin et al.
A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised Learning
Marco Fraccaro, Simon Kamronn, Ulrich Paquet et al.
Probabilistic Rule Realization and Selection
Haizi Yu, Tianxi Li, Lav R. Varshney
Neural Discrete Representation Learning
Aaron van den Oord, Oriol Vinyals, koray kavukcuoglu
Online Dynamic Programming
Holakou Rahmanian, Manfred K. Warmuth
Learning from uncertain curves: The 2-Wasserstein metric for Gaussian processes
Anton Mallasto, Aasa Feragen
Targeting EEG/LFP Synchrony with Neural Nets
Yitong Li, michael Murias, samantha Major et al.
Good Semi-supervised Learning That Requires a Bad GAN
Zihang Dai, Zhilin Yang, Fan Yang et al.
Union of Intersections (UoI) for Interpretable Data Driven Discovery and Prediction
Kristofer Bouchard, Alejandro Bujan, Fred Roosta et al.
Context Selection for Embedding Models
Liping Liu, Francisco Ruiz, Susan Athey et al.
Clone MCMC: Parallel High-Dimensional Gaussian Gibbs Sampling
Andrei-Cristian Barbos, Francois Caron, Jean-François Giovannelli et al.
Time-dependent spatially varying graphical models, with application to brain fMRI data analysis
Kristjan Greenewald, Seyoung Park, Shuheng Zhou et al.
Safe Model-based Reinforcement Learning with Stability Guarantees
Felix Berkenkamp, Matteo Turchetta, Angela Schoellig et al.
Learning with Feature Evolvable Streams
Bo-Jian Hou, Lijun Zhang, Zhi-Hua Zhou
Doubly Accelerated Stochastic Variance Reduced Dual Averaging Method for Regularized Empirical Risk Minimization
Tomoya Murata, Taiji Suzuki
Sobolev Training for Neural Networks
Wojciech M. Czarnecki, Simon Osindero, Max Jaderberg et al.
Hierarchical Attentive Recurrent Tracking
Adam Kosiorek, Alex Bewley, Ingmar Posner
VAIN: Attentional Multi-agent Predictive Modeling
Yedid Hoshen
Communication-Efficient Distributed Learning of Discrete Distributions
Ilias Diakonikolas, Elena Grigorescu, Jerry Li et al.
A Minimax Optimal Algorithm for Crowdsourcing
Thomas Bonald, Richard Combes