Papers
4,025 papers found
Actor-Critic Fictitious Play in Simultaneous Move Multistage Games
Julien Perolat, Bilal Piot, Olivier Pietquin
AdaGeo: Adaptive Geometric Learning for Optimization and Sampling
Gabriele Abbati, Alessandra Tosi, Michael Osborne et al.
Adaptive balancing of gradient and update computation times using global geometry and approximate subproblems
Sai Praneeth Reddy Karimireddy, Sebastian Stich, Martin Jaggi
Adaptive Sampling for Coarse Ranking
Sumeet Katariya, Lalit Jain, Nandana Sengupta et al.
A Fast Algorithm for Separated Sparsity via Perturbed Lagrangians
Aleksander Madry, Slobodan Mitrovic, Ludwig Schmidt
A fully adaptive algorithm for pure exploration in linear bandits
Liyuan Xu, Junya Honda, Masashi Sugiyama
A Generic Approach for Escaping Saddle points
Sashank Reddi, Manzil Zaheer, Suvrit Sra et al.
An Analysis of Categorical Distributional Reinforcement Learning
Mark Rowland, Marc Bellemare, Will Dabney et al.
A Nonconvex Proximal Splitting Algorithm under Moreau-Yosida Regularization
Emanuel Laude, Tao Wu, Daniel Cremers
An Optimization Approach to Learning Falling Rule Lists
Chaofan Chen, Cynthia Rudin
Approximate Ranking from Pairwise Comparisons
Reinhard Heckel, Max Simchowitz, Kannan Ramchandran et al.
A Provable Algorithm for Learning Interpretable Scoring Systems
Nataliya Sokolovska, Yann Chevaleyre, Jean-Daniel Zucker
A Simple Analysis for Exp-concave Empirical Minimization with Arbitrary Convex Regularizer
Tianbao Yang, Zhe Li, Lijun Zhang
A Stochastic Differential Equation Framework for Guiding Online User Activities in Closed Loop
Yichen Wang, Evangelos Theodorou, Apurv Verma et al.
Asynchronous Doubly Stochastic Group Regularized Learning
Bin Gu, Zhouyuan Huo, Heng Huang
A Unified Dynamic Approach to Sparse Model Selection
Chendi Huang, Yuan Yao
A Unified Framework for Nonconvex Low-Rank plus Sparse Matrix Recovery
Xiao Zhang, Lingxiao Wang, Quanquan Gu
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.
Bayesian Approaches to Distribution Regression
Ho Chung Leon Law, Danica J. Sutherland, Dino Sejdinovic et al.
Bayesian Multi-label Learning with Sparse Features and Labels, and Label Co-occurrences
He Zhao, Piyush Rai, Lan Du et al.
Bayesian Nonparametric Poisson-Process Allocation for Time-Sequence Modeling
Hongyi Ding, Mohammad Khan, Issei Sato et al.
Bayesian Structure Learning for Dynamic Brain Connectivity
Michael Andersen, Ole Winther, Lars Kai Hansen et al.
Beating Monte Carlo Integration: a Nonasymptotic Study of Kernel Smoothing Methods
Stephan Clémençon, François Portier