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
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
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