Papers
Cause-Effect Inference by Comparing Regression Errors
Patrick Bloebaum, Dominik Janzing, Takashi Washio et al.
Robust Maximization of Non-Submodular Objectives
Ilija Bogunovic, Junyao Zhao, Volkan Cevher
Smooth and Sparse Optimal Transport
Mathieu Blondel, Vivien Seguy, Antoine Rolet
Community Detection in Hypergraphs: Optimal Statistical Limit and Efficient Algorithms
I Chien, Chung-Yi Lin, I-Hsiang Wang
Human Interaction with Recommendation Systems
Sven Schmit, Carlos Riquelme
Contextual Bandits with Stochastic Experts
Rajat Sen, Karthikeyan Shanmugam, Sanjay Shakkottai
A fully adaptive algorithm for pure exploration in linear bandits
Liyuan Xu, Junya Honda, Masashi Sugiyama
Best arm identification in multi-armed bandits with delayed feedback
Aditya Grover, Todor Markov, Peter Attia et al.
Variational Rejection Sampling
Aditya Grover, Ramki Gummadi, Miguel Lazaro-Gredilla et al.
Variational Inference based on Robust Divergences
Futoshi Futami, Issei Sato, Masashi Sugiyama
Slow and Stale Gradients Can Win the Race: Error-Runtime Trade-offs in Distributed SGD
Sanghamitra Dutta, Gauri Joshi, Soumyadip Ghosh et al.
Random Warping Series: A Random Features Method for Time-Series Embedding
Lingfei Wu, Ian En-Hsu Yen, Jinfeng Yi et al.
One-shot Coresets: The Case of k-Clustering
Olivier Bachem, Mario Lucic, Silvio Lattanzi
Direct Learning to Rank And Rerank
Cynthia Rudin, Yining Wang
Stochastic Three-Composite Convex Minimization with a Linear Operator
Renbo Zhao, Volkan Cevher
Batched Large-scale Bayesian Optimization in High-dimensional Spaces
Zi Wang, Clement Gehring, Pushmeet Kohli et al.
Batch-Expansion Training: An Efficient Optimization Framework
Michal Derezinski, Dhruv Mahajan, S. Sathiya Keerthi et al.
Scalable Gaussian Processes with Billions of Inducing Inputs via Tensor Train Decomposition
Pavel Izmailov, Alexander Novikov, Dmitry Kropotov
Subsampling for Ridge Regression via Regularized Volume Sampling
Michal Derezinski, Manfred Warmuth
Tracking the gradients using the Hessian: A new look at variance reducing stochastic methods
Robert Gower, Nicolas Le Roux, Francis Bach
Variational inference for the multi-armed contextual bandit
Iñigo Urteaga, Chris Wiggins
Natural Gradients in Practice: Non-Conjugate Variational Inference in Gaussian Process Models
Hugh Salimbeni, Stefanos Eleftheriadis, James Hensman
Nonlinear Weighted Finite Automata
Tianyu Li, Guillaume Rabusseau, Doina Precup
Few-shot Generative Modelling with Generative Matching Networks
Sergey Bartunov, Dmitry Vetrov