4 papers · 1 filter
A Short Note on a Variant of the Squint Algorithm
Haipeng Luo
This short note describes a simple variant of the Squint algorithm of Koolen and Van Erven [2015] for the classic expert problem. Via an equally simple modification of their proof,…
Scale-Invariant Fast Convergence in Games
Taira Tsuchiya, Haipeng Luo, Shinji Ito
Scale-invariance in games has recently emerged as a widely valued desirable property. Yet, almost all fast convergence guarantees in learning in games require prior knowledge of th…
Online Learning for Uninformed Markov Games: Empirical Nash-Value Regret and Non-Stationarity Adaptation
Junyan Liu, Haipeng Luo, Zihan Zhang +1
We study online learning in two-player uninformed Markov games, where the opponent's actions and policies are unobserved. In this setting, Tian et al. (2021) show that achieving no…
Adversarial Learning in Games with Bandit Feedback: Logarithmic Pure-Strategy Maximin Regret
Shinji Ito, Haipeng Luo, Arnab Maiti +2
Learning to play zero-sum games is a fundamental problem in game theory and machine learning. While significant progress has been made in minimizing external regret in the self-pla…