Expected Sample Complexity in Multi-Armed Bandits

arXiv:2610.09929 · cs.LG, stat.ML · Submitted 2026-10-07 · Read on arXiv

cs.LG, stat.ML

Submitted: 2026-10-07

Updated: 2026-10-07

Terminology

• Sample Complexity — 88× in this paper · explained in 15 episodes
• Regret — 43× in this paper · explained in 3 episodes
• Reinforcement Learning — 7× in this paper · explained in 4 episodes
• Approximately Correct in Expectation — 4× in this paper
• Generative AI — 2× in this paper · explained in 2 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Action Space — 1× in this paper · explained in 1 episode
• Consistency — 1× in this paper · explained in 3 episodes
• Contextual Bandits — 1× in this paper · explained in 3 episodes
• Deep Reinforcement Learning — 1× in this paper · explained in 2 episodes
• EMMA — 1× in this paper · explained in 2 episodes
• Pruning — 1× in this paper · explained in 4 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Theoretical Guarantees — 1× in this paper · explained in 2 episodes

Sources

• A Survey on Practical Applications of Multi-Armed and Contextual Bandits
• The Definitive Guide to Policy Gradients in Deep Reinforcement Learning: Theory, Algorithms and Implementations
• Proximal Policy Optimization Algorithms

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