AI Paper Atlas

Research map / Bandits and online learning / Multi-armed bandits

Multiple-Play Stochastic Bandits with Shareable Finite-Capacity Arms

ICML 2022 · Bandits and online learning › Multi-armed bandits · approach: Non-stationary and structured-reward bandits · 1 citations (OpenAlex)

Read the paperCheck your idea against 108,967 papers

AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.

Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use OrchExplore instead of MP-SE-SA or ETC-UCBMP-MAB-SA · Bernoulli-reward simulationregretHelped
Use the proposed uniform confidence interval (UCI) instead of Hoeffding-based intervals (ablation)OrchExplore · Bernoulli-reward simulationregretHelped
Learn unknown capacities rather than use known capacities (ablation)OrchExplore · Bernoulli-reward simulationregretHurt
Model shareable arms explicitly and use OrchExplore instead of treating each allocation as an independent armMP-MAB-SA · Bernoulli-reward simulationregretHelped

Closest papers by meaning

Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.

Open scime draft

Get the next scime Dispatch and a monthly field update

Free. We send a confirmation link first; every email has a one-click unsubscribe. Privacy