No-regret algorithms in on-line learning, games and convex optimization

被引：1
|
作者：
Sorin, Sylvain [1 ]
机构：
[1] Sorbonne Univ, Inst Math Jussieu, CNRS UMR 7586, PRG, Campus Pierre Marie Curie, Paris, France
来源：
MATHEMATICAL PROGRAMMING | 2024年 / 203卷 / 1-2期
关键词：
68T05; 68W27; 68W50; 90C25; 91A26; PROJECTED SUBGRADIENT METHODS; DYNAMICAL-SYSTEMS; 1ST-ORDER METHODS; VARIATIONAL-INEQUALITIES; MONOTONE-OPERATORS; GRADIENT; CONVERGENCE; DESCENT; APPROXIMATIONS; MINIMIZATION;
D O I：
10.1007/s10107-023-01927-7
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
The purpose of this article is to underline the links between some no-regret algorithms used in on-line learning, games and convex optimization and to compare the continuous and discrete time versions.
引用
收藏
页码：645 / 686
页数：42
相关论文
共 50 条
  • [1] No-regret algorithms in on-line learning, games and convex optimization
    Sylvain Sorin
    Mathematical Programming, 2024, 203 : 645 - 686
  • [2] Risk-Averse No-Regret Learning in Online Convex Games
    Wang, Zifan
    Shen, Yi
    Zavlanos, Michael M.
    INTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 162, 2022,
  • [3] No-Regret Learning in Bayesian Games
    Hartline, Jason
    Syrgkanis, Vasilis
    Tardos, Eva
    ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 28 (NIPS 2015), 2015, 28
  • [4] Near-Optimal No-Regret Learning Dynamics for General Convex Games
    Farina, Gabriele
    Anagnostides, Ioannis
    Luo, Haipeng
    Lee, Chung-Wei
    Kroer, Christian
    Sandholm, Tuomas
    ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 35, NEURIPS 2022, 2022,
  • [5] Limits and limitations of no-regret learning in games
    Monnot, Barnabe
    Piliouras, Georgios
    KNOWLEDGE ENGINEERING REVIEW, 2017, 32
  • [6] No-Regret Learning in Dynamic Stackelberg Games
    Lauffer, Niklas
    Ghasemi, Mahsa
    Hashemi, Abolfazl
    Savas, Yagiz
    Topcu, Ufuk
    IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2024, 69 (03) : 1418 - 1431
  • [7] Doubly Optimal No-Regret Learning in Monotone Games
    Cai, Yang
    Zheng, Weiqiang
    INTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 202, 2023, 202
  • [8] No-Regret Learning and Equilibrium Computation in Quantum Games
    Lin, Wayne
    Piliouras, Georgios
    Sim, Ryann
    Varvitsiotis, Antonios
    QUANTUM, 2024, 8
  • [9] No-Regret Learning in Unknown Games with Correlated Payoffs
    Sessa, Pier Giuseppe
    Bogunovic, Ilija
    Kamgarpour, Maryam
    Krause, Andreas
    ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 32 (NIPS 2019), 2019, 32
  • [10] Sampling Equilibria: Fast No-Regret Learning in Structured Games
    Beaglehole, Daniel
    Hopkins, Max
    Kane, Daniel
    Liu, Sihan
    Lovett, Shachar
    PROCEEDINGS OF THE 2023 ANNUAL ACM-SIAM SYMPOSIUM ON DISCRETE ALGORITHMS, SODA, 2023, : 3817 - 3855
12345