Papers
PAC-Bayesian Bounds based on the Rényi Divergence
Luc Bégin, Pascal Germain, François Laviolette et al.
Parallel Majorization Minimization with Dynamically Restricted Domains for Nonconvex Optimization
Yan Kaganovsky, Ikenna Odinaka, David Carlson et al.
Parallel Markov Chain Monte Carlo via Spectral Clustering
Guillaume Basse, Aaron Smith, Natesh Pillai
Pareto Front Identification from Stochastic Bandit Feedback
Peter Auer, Chao-Kai Chiang, Ronald Ortner et al.
Precision Matrix Estimation in High Dimensional Gaussian Graphical Models with Faster Rates
Lingxiao Wang, Xiang Ren, Quanquan Gu
Private Causal Inference
Matt J. Kusner, Yu Sun, Karthik Sridharan et al.
Probabilistic Approximate Least-Squares
Simon Bartels, Philipp Hennig
Provable Bayesian Inference via Particle Mirror Descent
Bo Dai, Niao He, Hanjun Dai et al.
Provable Tensor Methods for Learning Mixtures of Generalized Linear Models
Hanie Sedghi, Majid Janzamin, Anima Anandkumar
Pseudo-Marginal Slice Sampling
Iain Murray, Matthew Graham
Quantization based Fast Inner Product Search
Ruiqi Guo, Sanjiv Kumar, Krzysztof Choromanski et al.
Random Forest for the Contextual Bandit Problem
Raphaël Féraud, Robin Allesiardo, Tanguy Urvoy et al.
Randomization and The Pernicious Effects of Limited Budgets on Auction Experiments
Guillaume W. Basse, Hossein Azari Soufiani, Diane Lambert
Revealing Graph Bandits for Maximizing Local Influence
Alexandra Carpentier, Michal Valko
Rivalry of Two Families of Algorithms for Memory-Restricted Streaming PCA
Chun-Liang Li, Hsuan-Tien Lin, Chi-Jen Lu
Robust Covariate Shift Regression
Xiangli Chen, Mathew Monfort, Anqi Liu et al.
Scalable and Sound Low-Rank Tensor Learning
Hao Cheng, Yaoliang Yu, Xinhua Zhang et al.
Scalable Exemplar Clustering and Facility Location via Augmented Block Coordinate Descent with Column Generation
Ian En-Hsu Yen, Dmitry Malioutov, Abhishek Kumar
Scalable Gaussian Process Classification via Expectation Propagation
Daniel Hernandez-Lobato, Jose Miguel Hernandez-Lobato
Scalable Gaussian Processes for Characterizing Multidimensional Change Surfaces
William Herlands, Andrew Wilson, Hannes Nickisch et al.
Scalable geometric density estimation
Ye Wang, Antonio Canale, David Dunson
Scalable MCMC for Mixed Membership Stochastic Blockmodels
Wenzhe Li, Sungjin Ahn, Max Welling