Papers
Expectation Propagation for t-Exponential Family Using q-Algebra
Futoshi Futami, Issei Sato, Masashi Sugiyama
Unifying PAC and Regret: Uniform PAC Bounds for Episodic Reinforcement Learning
Christoph Dann, Tor Lattimore, Emma Brunskill
Phase Transitions in the Pooled Data Problem
Jonathan Scarlett, Volkan Cevher
Semi-Supervised Learning for Optical Flow with Generative Adversarial Networks
Wei-Sheng Lai, Jia-Bin Huang, Ming-Hsuan Yang
Efficient Modeling of Latent Information in Supervised Learning using Gaussian Processes
Zhenwen Dai, Mauricio Álvarez, Neil Lawrence
Learning Linear Dynamical Systems via Spectral Filtering
Elad Hazan, Karan Singh, Cyril Zhang
Aggressive Sampling for Multi-class to Binary Reduction with Applications to Text Classification
Bikash Joshi, Massih R. Amini, Ioannis Partalas et al.
Neural Variational Inference and Learning in Undirected Graphical Models
Volodymyr Kuleshov, Stefano Ermon
Learning to Model the Tail
Yu-Xiong Wang, Deva Ramanan, Martial Hebert
k-Support and Ordered Weighted Sparsity for Overlapping Groups: Hardness and Algorithms
Cong Han Lim, Stephen Wright
Diffusion Approximations for Online Principal Component Estimation and Global Convergence
Chris Junchi Li, Mengdi Wang, Han Liu et al.
A Universal Analysis of Large-Scale Regularized Least Squares Solutions
Ashkan Panahi, Babak Hassibi
Dualing GANs
Yujia Li, Alexander Schwing, Kuan-Chieh Wang et al.
When Worlds Collide: Integrating Different Counterfactual Assumptions in Fairness
Chris Russell, Matt J Kusner, Joshua Loftus et al.
Hybrid Reward Architecture for Reinforcement Learning
Harm Van Seijen, Mehdi Fatemi, Joshua Romoff et al.
Introspective Classification with Convolutional Nets
Long Jin, Justin Lazarow, Zhuowen Tu
Safe Adaptive Importance Sampling
Sebastian U Stich, Anant Raj, Martin Jaggi
Spherical convolutions and their application in molecular modelling
Wouter Boomsma, Jes Frellsen
Exploring Generalization in Deep Learning
Behnam Neyshabur, Srinadh Bhojanapalli, David Mcallester et al.
Robust Optimization for Non-Convex Objectives
Robert S. Chen, Brendan Lucier, Yaron Singer et al.
Estimation of the covariance structure of heavy-tailed distributions
Xiaohan Wei, Stanislav Minsker
Identification of Gaussian Process State Space Models
Stefanos Eleftheriadis, Tom Nicholson, Marc Deisenroth et al.
Nonlinear random matrix theory for deep learning
Jeffrey Pennington, Pratik Worah
Continual Learning with Deep Generative Replay
Hanul Shin, Jung Kwon Lee, Jaehong Kim et al.