Papers
Learning Nash Equilibrium for General-Sum Markov Games from Batch Data
Julien Perolat, Florian Strub, Bilal Piot et al.
Near-optimal Bayesian Active Learning with Correlated and Noisy Tests
Yuxin Chen, Hamed Hassani, Andreas Krause
Learning Theory for Conditional Risk Minimization
Alexander Zimin, Christoph Lampert
Estimating Density Ridges by Direct Estimation of Density-Derivative-Ratios
Hiroaki Sasaki, Takafumi Kanamori, Masashi Sugiyama
Minimax Density Estimation for Growing Dimension
Daniel McDonald
A Sub-Quadratic Exact Medoid Algorithm
James Newling, Francois Fleuret
Linear Thompson Sampling Revisited
Marc Abeille, Alessandro Lazaric
Learning Cost-Effective and Interpretable Treatment Regimes
Himabindu Lakkaraju, Cynthia Rudin
Learning Time Series Detection Models from Temporally Imprecise Labels
Roy Adams, Ben Marlin
Less than a Single Pass: Stochastically Controlled Stochastic Gradient
Lihua Lei, Michael Jordan
Annular Augmentation Sampling
Francois Fagan, Jalaj Bhandari, John Cunningham
Consistent and Efficient Nonparametric Different-Feature Selection
Satoshi Hara, Takayuki Katsuki, Hiroki Yanagisawa et al.
Tensor-Dictionary Learning with Deep Kruskal-Factor Analysis
Andrew Stevens, Yunchen Pu, Yannan Sun et al.
Guaranteed Non-convex Optimization: Submodular Maximization over Continuous Domains
Andrew An Bian, Baharan Mirzasoleiman, Joachim Buhmann et al.
Nearly Instance Optimal Sample Complexity Bounds for Top-k Arm Selection
Lijie Chen, Jian Li, Mingda Qiao
On the Learnability of Fully-Connected Neural Networks
Yuchen Zhang, Jason Lee, Martin Wainwright et al.
Sparse Accelerated Exponential Weights
Pierre Gaillard, Olivier Wintenberger
Non-square matrix sensing without spurious local minima via the Burer-Monteiro approach
Dohyung Park, Anastasios Kyrillidis, Constantine Carmanis et al.
Lower Bounds on Active Learning for Graphical Model Selection
Jonathan Scarlett, Volkan Cevher
ASAGA: Asynchronous Parallel SAGA
Rémi Leblond, Fabian Pedregosa, Simon Lacoste-Julien
Online Nonnegative Matrix Factorization with General Divergences
Renbo Zhao, Vincent Tan, Huan Xu
Clustering from Multiple Uncertain Experts
Yale Chang, Junxiang Chen, Michael Cho et al.
Large-Scale Data-Dependent Kernel Approximation
Catalin Ionescu, Alin Popa, Cristian Sminchisescu
Conditions beyond treewidth for tightness of higher-order LP relaxations
Mark Rowland, Aldo Pacchiano, Adrian Weller