52 citations · 52 across the 5 of their papers we have counts for
4 papers · 1 filter
Gaussian-Width Bounds for Offline-to-Online Linear Bandits
Kushagra Chandak, Volodymyr Tkachuk, Xiaoqi Tan +1
We study how offline data can help online learning in stochastic linear bandits. We focus on partially covered offline data, where only of the feature directions are poorly…
Offline-to-Online Learning in Linear Bandits
Kushagra Chandak, Toshinori Kitamura, Xiaoqi Tan
We study online learning with an additional offline dataset in the stochastic linear bandit setting. Although this problem arises frequently in practice, the offline-to-online trad…
Context-Action Embedding Learning for Off-Policy Evaluation in Contextual Bandits
Kushagra Chandak, Vincent Liu, Haanvid Lee
We consider off-policy evaluation (OPE) in contextual bandits with finite action space. Inverse Propensity Score (IPS) weighting is a widely used method for OPE due to its unbiased…
Regret Minimization via Saddle Point Optimization
Johannes Kirschner, Seyed Alireza Bakhtiari, Kushagra Chandak +2
A long line of works characterizes the sample complexity of regret minimization in sequential decision-making by min-max programs. In the corresponding saddle-point game, the min-p…