7 citations · 19 across the 31 of their papers we have counts for
5 papers · 1 filter
Best-of-Both-Worlds Algorithms for Partial Monitoring
Taira Tsuchiya, Shinji Ito, Junya Honda
This study considers the partial monitoring problem with -actions and -outcomes and provides the first best-of-both-worlds algorithms, whose regrets are favorably bounded bot…
Adversarially Robust Multi-Armed Bandit Algorithm with Variance-Dependent Regret Bounds
Shinji Ito, Taira Tsuchiya, Junya Honda
This paper considers the multi-armed bandit (MAB) problem and provides a new best-of-both-worlds (BOBW) algorithm that works nearly optimally in both stochastic and adversarial set…
Nearly Optimal Best-of-Both-Worlds Algorithms for Online Learning with Feedback Graphs
Shinji Ito, Taira Tsuchiya, Junya Honda
This study considers online learning with general directed feedback graphs. For this problem, we present best-of-both-worlds algorithms that achieve nearly tight regret bounds for…
Online Task Assignment Problems with Reusable Resources
Hanna Sumita, Shinji Ito, Kei Takemura +4
We study online task assignment problem with reusable resources, motivated by practical applications such as ridesharing, crowdsourcing and job hiring. In the problem, we are given…
Single Loop Gaussian Homotopy Method for Non-convex Optimization
Hidenori Iwakiri, Yuhang Wang, Shinji Ito +1
The Gaussian homotopy (GH) method is a popular approach to finding better stationary points for non-convex optimization problems by gradually reducing a parameter value , which…