Research map / Bandits and online learning / Multi-armed bandits
Single-pass Streaming Lower Bounds for Multi-armed Bandits Exploration with Instance-sensitive Sample Complexity
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.
Closest papers by meaning
- Nearly Tight Bounds for Exploration in Streaming Multi-Armed Bandits with Known Optimality Gap (AAAI 2025 · similarity 0.94)
- Tight Regret Bounds for Single-pass Streaming Multi-armed Bandits (ICML 2023 · similarity 0.91)
- The Batch Complexity of Bandit Pure Exploration (ICML 2025 · similarity 0.88)
- Linear Streaming Bandit: Regret Minimization and Fixed-Budget Epsilon-Best Arm Identification (AAAI 2025 · similarity 0.87)
- Near Optimal Non-asymptotic Sample Complexity of 1-Identification (ICML 2025 · similarity 0.87)
- Thompson Sampling for Real-Valued Combinatorial Pure Exploration of Multi-Armed Bandit (AAAI 2024 · similarity 0.86)
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.