Lalit Jain

most citedFinding All ε-Good Arms in Stochastic Bandits

6 citations · 7 across the 2 of their papers we have counts for

collaborators

Showing stat.MLShow all

2 papers · 1 filter

stat.ML2023★ 2 cited

Optimal Exploration is no harder than Thompson Sampling

Zhaoqi Li, Kevin Jamieson, Lalit Jain

Given a set of arms $Z \subset R^{d}$ and an unknown parameter vector $θ_{*} \in R^{d}$ , the pure exploration linear bandit problem aims to return $\arg\max_{…

stat.ML2020★ 6 cited

Finding All ε-Good Arms in Stochastic Bandits

Blake Mason, Lalit Jain, Ardhendu Tripathy +1

The pure-exploration problem in stochastic multi-armed bandits aims to find one or more arms with the largest (or near largest) means. Examples include finding an ε-good arm, best-…