Papers
Stochastic Block BFGS: Squeezing More Curvature out of Data
Robert Gower, Donald Goldfarb, Peter Richtarik
Softened Approximate Policy Iteration for Markov Games
Julien Pérolat, Bilal Piot, Matthieu Geist et al.
The knockoff filter for FDR control in group-sparse and multitask regression
Ran Dai, Rina Barber
Meta-Learning with Memory-Augmented Neural Networks
Adam Santoro, Sergey Bartunov, Matthew Botvinick et al.
On Graduated Optimization for Stochastic Non-Convex Problems
Elad Hazan, Kfir Yehuda Levy, Shai Shalev-Shwartz
SDNA: Stochastic Dual Newton Ascent for Empirical Risk Minimization
Zheng Qu, Peter Richtarik, Martin Takac et al.
No penalty no tears: Least squares in high-dimensional linear models
Xiangyu Wang, David Dunson, Chenlei Leng
Opponent Modeling in Deep Reinforcement Learning
He He, Jordan Boyd-Graber, Kevin Kwok et al.
Hierarchical Compound Poisson Factorization
Mehmet Basbug, Barbara Engelhardt
Stochastic Optimization for Multiview Representation Learning using Partial Least Squares
Raman Arora, Poorya Mianjy, Teodor Marinov
Train and Test Tightness of LP Relaxations in Structured Prediction
Ofer Meshi, Mehrdad Mahdavi, Adrian Weller et al.
Gaussian quadrature for matrix inverse forms with applications
Chengtao Li, Suvrit Sra, Stefanie Jegelka
Why Most Decisions Are Easy in Tetris—And Perhaps in Other Sequential Decision Problems, As Well
Özgür Şimşek, Simón Algorta, Amit Kothiyal
Pixel Recurrent Neural Networks
Aäron van den Oord, Nal Kalchbrenner, Koray Kavukcuoglu
Dictionary Learning for Massive Matrix Factorization
Arthur Mensch, Julien Mairal, Bertrand Thirion et al.
Neural Variational Inference for Text Processing
Yishu Miao, Lei Yu, Phil Blunsom
Learning Granger Causality for Hawkes Processes
Hongteng Xu, Mehrdad Farajtabar, Hongyuan Zha
Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteriors
Christos Louizos, Max Welling
Fast Parameter Inference in Nonlinear Dynamical Systems using Iterative Gradient Matching
Mu Niu, Simon Rogers, Maurizio Filippone et al.
An optimal algorithm for the Thresholding Bandit Problem
Andrea Locatelli, Maurilio Gutzeit, Alexandra Carpentier
ForecastICU: A Prognostic Decision Support System for Timely Prediction of Intensive Care Unit Admission
Jinsung Yoon, Ahmed Alaa, Scott Hu et al.
Recommendations as Treatments: Debiasing Learning and Evaluation
Tobias Schnabel, Adith Swaminathan, Ashudeep Singh et al.
Matrix Eigen-decomposition via Doubly Stochastic Riemannian Optimization
Zhiqiang Xu, Peilin Zhao, Jianneng Cao et al.
Extended and Unscented Kitchen Sinks
Edwin Bonilla, Daniel Steinberg, Alistair Reid
No-Regret Algorithms for Heavy-Tailed Linear Bandits
Andres Munoz Medina, Scott Yang