{"total":12,"rows":[{"id":"2306.04923","title":"Unconstrained Online Learning with Unbounded Losses","created":"2023-06-08","cited_by_count":25,"area":null},{"id":"2310.18554","title":"Improved Regret Bounds of (Multinomial) Logistic Bandits via Regret-to-Confidence-Set Conversion","created":"2023-10-28","cited_by_count":24,"area":null},{"id":"2211.01357","title":"Quasi-Newton Steps for Efficient Online Exp-Concave Optimization","created":"2022-11-02","cited_by_count":10,"area":null},{"id":"2405.19175","title":"Online Linear Regression in Dynamic Environments via Discounting","created":"2024-05-29","cited_by_count":10,"area":null},{"id":"2405.20540","title":"Fully Unconstrained Online Learning","created":"2024-05-30","cited_by_count":10,"area":null},{"id":"2506.10616","title":"Non-stationary Online Learning for Curved Losses: Improved Dynamic Regret via Mixability","created":"2025-06-12","cited_by_count":7,"area":null},{"id":"2402.07341","title":"Noise-Adaptive Confidence Sets for Linear Bandits and Application to Bayesian Optimization","created":"2024-02-12","cited_by_count":6,"area":null},{"id":"2506.07595","title":"Exploiting Curvature in Online Convex Optimization with Delayed Feedback","created":"2025-06-09","cited_by_count":6,"area":null},{"id":"2205.03728","title":"Precise Regret Bounds for Log-loss via a Truncated Bayesian Algorithm","created":"2022-05-07","cited_by_count":5,"area":null},{"id":"2507.05478","title":"Dynamic Regret Reduces to Kernelized Static Regret","created":"2025-07-07","cited_by_count":5,"area":null},{"id":"2602.08372","title":"Dynamic Regret via Discounted-to-Dynamic Reduction with Applications to Curved Losses and Adam Optimizer","created":"2026-02-09","cited_by_count":4,"area":null},{"id":"2310.01756","title":"Improved Algorithms for Adversarial Bandits with Unbounded Losses","created":"2023-10-03","cited_by_count":3,"area":null}],"next_cursor":null}