Blackwell Approachability and Low-Regret Learning are Equivalent

8 November 2010

Papers citing "Blackwell Approachability and Low-Regret Learning are Equivalent"

11 / 11 papers shown

Title
Constrained Online Decision-Making: A Unified Framework Haichen Hu David Simchi-Levi Navid Azizan 31 0 0 11 May 2025
Calibrated Probabilistic Forecasts for Arbitrary Sequences Charles Marx Volodymyr Kuleshov Stefano Ermon AI4TS 36 1 0 27 Sep 2024
Rate-Preserving Reductions for Blackwell Approachability Christoph Dann Yishay Mansour M. Mohri Jon Schneider Balasubramanian Sivan 42 2 0 10 Jun 2024
Pseudonorm Approachability and Applications to Regret Minimization Christoph Dann Yishay Mansour M. Mohri Jon Schneider Balasubramanian Sivan 26 5 0 03 Feb 2023
Near-Optimal No-Regret Learning for Correlated Equilibria in Multi-Player General-Sum Games Ioannis Anagnostides C. Daskalakis Gabriele Farina Maxwell Fishelson Noah Golowich T. Sandholm 54 53 0 11 Nov 2021
Learning and Information in Stochastic Networks and Queues N. Walton Kuang Xu 13 20 0 18 May 2021
Blackwell Online Learning for Markov Decision Processes Tao Li Guanze Peng Quanyan Zhu OffRL 11 16 0 28 Dec 2020
Reinforcement Learning with Convex Constraints Sobhan Miryoosefi Kianté Brantley Hal Daumé Miroslav Dudík Robert Schapire 17 90 0 21 Jun 2019
Online Learning with Continuous Variations: Dynamic Regret and Reductions Ching-An Cheng Jonathan Lee Ken Goldberg Byron Boots 26 16 0 19 Feb 2019
Lazy-CFR: fast and near optimal regret minimization for extensive games with imperfect information Yichi Zhou Tongzheng Ren J. Li Dong Yan Jun Zhu 8 13 0 10 Oct 2018
Regret Minimization in Behaviorally-Constrained Zero-Sum Games Gabriele Farina Christian Kroer T. Sandholm 20 23 0 09 Nov 2017