{"total":35,"rows":[{"id":"2102.05406","title":"Non-stationary Reinforcement Learning without Prior Knowledge: An Optimal Black-box Approach","created":"2021-02-10","cited_by_count":98,"area":null},{"id":"2112.14368","title":"Adaptivity and Non-stationarity: Problem-dependent Dynamic Regret for Online Convex Optimization","created":"2021-12-29","cited_by_count":66,"area":null},{"id":"2102.01046","title":"Impossible Tuning Made Possible: A New Expert Algorithm and Its Applications","created":"2021-02-01","cited_by_count":52,"area":null},{"id":"2201.12736","title":"No-Regret Learning in Time-Varying Zero-Sum Games","created":"2022-01-30","cited_by_count":36,"area":null},{"id":"2102.03758","title":"Non-stationary Online Learning with Memory and Non-stochastic Control","created":"2021-02-07","cited_by_count":33,"area":null},{"id":"2110.13282","title":"The Pareto Frontier of model selection for general Contextual Bandits","created":"2021-10-25","cited_by_count":24,"area":null},{"id":"2409.05181","title":"Sliding-Window Thompson Sampling for Non-Stationary Settings","created":"2024-09-08","cited_by_count":17,"area":null},{"id":"2207.02829","title":"Online Bilevel Optimization: Regret Analysis of Online Alternating Gradient Methods","created":"2022-07-06","cited_by_count":15,"area":null},{"id":"2302.02552","title":"Adapting to Continuous Covariate Shift via Online Density Ratio Estimation","created":"2023-02-06","cited_by_count":15,"area":null},{"id":"2305.17301","title":"Stability-penalty-adaptive follow-the-regularized-leader: Sparsity, game-dependency, and best-of-both-worlds","created":"2023-05-26","cited_by_count":15,"area":null},{"id":"2408.09074","title":"Gradient-Variation Online Learning under Generalized Smoothness","created":"2024-08-17","cited_by_count":11,"area":null},{"id":"2307.08360","title":"Universal Online Learning with Gradient Variations: A Multi-layer Online Ensemble Approach","created":"2023-07-17","cited_by_count":9,"area":null},{"id":"2102.00725","title":"Generalized non-stationary bandits","created":"2021-02-01","cited_by_count":8,"area":null},{"id":"2107.11419","title":"Finite-time Analysis of Globally Nonstationary Multi-Armed Bandits","created":"2021-07-23","cited_by_count":7,"area":null},{"id":"2602.04761","title":"Improved Dimension Dependence for Bandit Convex Optimization with Gradient Variations","created":"2026-02-04","cited_by_count":5,"area":null},{"id":"2105.03681","title":"Universal Online Convex Optimization Meets Second-order Bounds","created":"2021-05-08","cited_by_count":4,"area":null},{"id":"2104.02822","title":"Low-Regret Active learning","created":"2021-04-06","cited_by_count":3,"area":null},{"id":"2210.14998","title":"One Arrow, Two Kills: An Unified Framework for Achieving Optimal Regret Guarantees in Sleeping Bandits","created":"2022-10-26","cited_by_count":3,"area":null},{"id":"2201.00486","title":"Using Non-Stationary Bandits for Learning in Repeated Cournot Games with Non-Stationary Demand","created":"2022-01-03","cited_by_count":2,"area":null},{"id":"2403.10732","title":"Variance-Dependent Regret Bounds for Non-stationary Linear Bandits","created":"2024-03-15","cited_by_count":2,"area":null},{"id":"2604.21432","title":"A single algorithm for both restless and rested rotting bandits","created":"2026-04-23","cited_by_count":2,"area":null},{"id":"2606.03831","title":"Online Learning with Gradient-Variation Interval Regret","created":"2026-06-02","cited_by_count":2,"area":null},{"id":"2302.09440","title":"Online Continuous Hyperparameter Optimization for Generalized Linear Contextual Bandits","created":"2023-02-18","cited_by_count":1,"area":null},{"id":"2303.02504","title":"MNL-Bandit in non-stationary environments","created":"2023-03-04","cited_by_count":1,"area":null},{"id":"2303.06552","title":"Energy Regularized RNNs for Solving Non-Stationary Bandit Problems","created":"2023-03-12","cited_by_count":1,"area":null},{"id":"2308.02734","title":"Learning to Schedule in Non-Stationary Wireless Networks With Unknown Statistics","created":"2023-08-04","cited_by_count":1,"area":null},{"id":"2310.07786","title":"Non-Stationary Contextual Bandit Learning via Neural Predictive Ensemble Sampling","created":"2023-10-11","cited_by_count":1,"area":null},{"id":"2602.07418","title":"Achieving Optimal Static and Dynamic Regret Simultaneously in Bandits with Deterministic Losses","created":"2026-02-07","cited_by_count":1,"area":null},{"id":"2609.20968","title":"From Switching to Dynamic Regret: A Simple Reduction via Unbiased Random Sequences","created":"2026-09-17","cited_by_count":1,"area":null},{"id":"2110.12544","title":"Online estimation and control with optimal pathlength regret","created":"2021-10-24","cited_by_count":0,"area":null},{"id":"2202.05996","title":"Mixture of Online and Offline Experts for Non-stationary Time Series","created":"2022-02-12","cited_by_count":0,"area":null},{"id":"2211.04586","title":"Learning to Price Supply Chain Contracts against a Learning Retailer","created":"2022-11-02","cited_by_count":0,"area":null},{"id":"2505.21095","title":"Improved Impossible Tuning and Lipschitz-Adaptive Universal Online Learning with Gradient Variations","created":"2025-05-27","cited_by_count":0,"area":null},{"id":"2511.05620","title":"Fooling Algorithms in Non-Stationary Bandits using Belief Inertia","created":"2025-11-06","cited_by_count":0,"area":null},{"id":"2605.21263","title":"Nonparametric Learning and Earning with One-Point Feedback under Nonstationarity","created":"2026-05-20","cited_by_count":0,"area":null}],"next_cursor":null}