The Cost of Adaptivity: Matching Lower Bounds Across Learning Problems

arXiv:2608.08826 · cs.LG · Submitted 2026-08-09 · Read on arXiv

Ibne Farabi Shihab, Adria Binte Habib

cs.LG

Submitted: 2026-08-09

Updated: 2026-08-11

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Robustness — 18× in this paper · explained in 6 episodes
• Regret — 12× in this paper · explained in 4 episodes
• Benchmark — 10× in this paper · explained in 2 episodes
• Composition — 10× in this paper · explained in 2 episodes
• Conference on Learning Theory — 4× in this paper
• Active Learning — 3× in this paper · explained in 6 episodes
• Journal of Machine Learning Research — 3× in this paper
• Post-Selection — 2× in this paper · explained in 3 episodes
• Regret Bound — 2× in this paper · explained in 2 episodes
• Regret Bounds — 2× in this paper · explained in 2 episodes
• Reinforcement Learning — 2× in this paper · explained in 4 episodes
• Ablation — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 3 episodes
• Bayesian Optimization — 1× in this paper · explained in 3 episodes
• Benchmarking — 1× in this paper · explained in 4 episodes
• Calibration — 1× in this paper · explained in 9 episodes
• Communication Complexity — 1× in this paper · explained in 3 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Homogeneity — 1× in this paper · explained in 2 episodes
• In International Conference on Machine Learning — 1× in this paper
• Inflation — 1× in this paper · explained in 2 episodes

Sources

• Online Learning: A Modern Introduction Using Convex Optimization

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