Oracle-Efficient and Parameter-Free Agnostic Smoothed Online Learning

arXiv:2610.10499 · cs.LG, stat.ML · Submitted 2026-10-07 · Read on arXiv

cs.LG, stat.ML

Submitted: 2026-10-07

Updated: 2026-10-07

Terminology

• Regret — 48× in this paper · explained in 3 episodes
• VC Dimension — 22× in this paper · explained in 2 episodes
• Adam — 11× in this paper · explained in 2 episodes
• Generalization — 5× in this paper · explained in 13 episodes
• Differentially Private — 2× in this paper · explained in 3 episodes
• Loss Function — 2× in this paper · explained in 2 episodes
• Reinforcement Learning — 2× in this paper · explained in 4 episodes
• Abstraction — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Decoupling — 1× in this paper · explained in 2 episodes
• Exchangeability — 1× in this paper · explained in 2 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Homogeneity — 1× in this paper · explained in 2 episodes
• Online Reinforcement Learning — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Sample Complexity — 1× in this paper · explained in 15 episodes

Sources

• Oracle-Efficient Online Classification with Stochastic Inputs and Adversarial Outputs
• The Statistical Complexity of Interactive Decision Making
• The Role of Coverage in Online Reinforcement Learning

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