Optimal High-Probability Regret for Online Convex Optimization with Two-Point Bandit Feedback
Optimal High-Probability Regret for Online Convex Optimization with Two-Point Bandit Feedback explores This paper develops a theoretical framework for online convex optimization with limited feedback, achieving optimal regret bounds.. Commercial viability score: 2/10 in Online Convex Optimization.
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