{"total":55,"rows":[{"id":"2207.10786","title":"Delayed Feedback in Generalised Linear Bandits Revisited","created":"2022-07-21","cited_by_count":23,"area":null},{"id":"2201.13172","title":"Near-Optimal Regret for Adversarial MDP with Delayed Bandit Feedback","created":"2022-01-31","cited_by_count":22,"area":null},{"id":"2112.02866","title":"Nonstochastic Bandits with Composite Anonymous Feedback","created":"2021-12-06","cited_by_count":16,"area":null},{"id":"2305.08629","title":"A Unified Analysis of Nonstochastic Delayed Feedback for Combinatorial Semi-Bandits, Linear Bandits, and MDPs","created":"2023-05-15","cited_by_count":15,"area":null},{"id":"2103.04550","title":"No Weighted-Regret Learning in Adversarial Bandits with Delays","created":"2021-03-08","cited_by_count":12,"area":null},{"id":"2206.09341","title":"Bayesian Optimization under Stochastic Delayed Feedback","created":"2022-06-19","cited_by_count":10,"area":null},{"id":"2302.00392","title":"Delayed Feedback in Kernel Bandits","created":"2023-02-01","cited_by_count":10,"area":null},{"id":"2107.00680","title":"A Map of Bandits for E-commerce","created":"2021-07-01","cited_by_count":9,"area":null},{"id":"2211.14720","title":"Rectified Pessimistic-Optimistic Learning for Stochastic Continuum-armed Bandit with Constraints","created":"2022-11-27","cited_by_count":9,"area":null},{"id":"2301.10500","title":"Banker Online Mirror Descent: A Universal Approach for Delayed Online Bandit Learning","created":"2023-01-25","cited_by_count":7,"area":null},{"id":"2302.01477","title":"A Reduction-based Framework for Sequential Decision Making with Delayed Feedback","created":"2023-02-03","cited_by_count":7,"area":null},{"id":"2402.11800","title":"Stochastic Approximation with Delayed Updates: Finite-Time Rates under Markovian Sampling","created":"2024-02-19","cited_by_count":7,"area":"deeprl"},{"id":"2502.12528","title":"Contextual Linear Bandits with Delay as Payoff","created":"2025-02-18","cited_by_count":7,"area":null},{"id":"2202.12431","title":"Thompson Sampling with Unrestricted Delays","created":"2022-02-24","cited_by_count":6,"area":null},{"id":"2305.07911","title":"Delay-Adapted Policy Optimization and Improved Regret for Adversarial MDP with Delayed Bandit Feedback","created":"2023-05-13","cited_by_count":6,"area":null},{"id":"2408.15158","title":"Delay as Payoff in MAB","created":"2024-08-27","cited_by_count":6,"area":null},{"id":"2111.07615","title":"Optimism and Delays in Episodic Reinforcement Learning","created":"2021-11-15","cited_by_count":5,"area":null},{"id":"2202.06694","title":"Versatile Dueling Bandits: Best-of-both-World Analyses for Online Learning from Preferences","created":"2022-02-14","cited_by_count":5,"area":null},{"id":"2306.08803","title":"Langevin Thompson Sampling with Logarithmic Communication: Bandits and Reinforcement Learning","created":"2023-06-15","cited_by_count":5,"area":null},{"id":"2510.09127","title":"Regret Bounds for Adversarial Contextual Bandits with General Function Approximation and Delayed Feedback","created":"2025-10-10","cited_by_count":5,"area":null},{"id":"2105.10590","title":"Parallelizing Contextual Bandits","created":"2021-05-21","cited_by_count":4,"area":null},{"id":"2306.01243","title":"Efficient Reinforcement Learning with Impaired Observability: Learning to Act with Delayed and Missing State Observations","created":"2023-06-02","cited_by_count":4,"area":null},{"id":"2405.16843","title":"Non-stochastic Bandits With Evolving Observations","created":"2024-05-27","cited_by_count":4,"area":null},{"id":"2202.06657","title":"The Impact of Batch Learning in Stochastic Linear Bandits","created":"2022-02-14","cited_by_count":3,"area":null},{"id":"2211.08997","title":"Dynamical Linear Bandits","created":"2022-11-16","cited_by_count":3,"area":null},{"id":"2305.18511","title":"Contextual Bandits with Budgeted Information Reveal","created":"2023-05-29","cited_by_count":3,"area":null},{"id":"2310.18919","title":"Posterior Sampling with Delayed Feedback for Reinforcement Learning with Linear Function Approximation","created":"2023-10-29","cited_by_count":3,"area":null},{"id":"2408.14603","title":"Biased Dueling Bandits with Stochastic Delayed Feedback","created":"2024-08-26","cited_by_count":3,"area":null},{"id":"2106.11294","title":"Smooth Sequential Optimisation with Delayed Feedback","created":"2021-06-21","cited_by_count":2,"area":null},{"id":"2202.00846","title":"Adaptive Experimentation with Delayed Binary Feedback","created":"2022-02-02","cited_by_count":2,"area":null},{"id":"2206.00586","title":"Multi-Armed Bandit Problem with Temporally-Partitioned Rewards: When Partial Feedback Counts","created":"2022-06-01","cited_by_count":2,"area":null},{"id":"2206.07126","title":"Lazy Queries Can Reduce Variance in Zeroth-order Optimization","created":"2022-06-14","cited_by_count":2,"area":null},{"id":"2302.06916","title":"Effective Dimension in Bandit Problems under Censorship","created":"2023-02-14","cited_by_count":2,"area":null},{"id":"2303.11582","title":"Adaptive Experimentation at Scale: A Computational Framework for Flexible Batches","created":"2023-03-21","cited_by_count":2,"area":null},{"id":"2305.02527","title":"Reinforcement Learning with Delayed, Composite, and Partially Anonymous Reward","created":"2023-05-04","cited_by_count":2,"area":null},{"id":"2402.05144","title":"A Bandit Approach with Evolutionary Operators for Model Selection","created":"2024-02-07","cited_by_count":2,"area":null},{"id":"2505.24193","title":"Improved Best-of-Both-Worlds Regret for Bandits with Delayed Feedback","created":"2025-05-30","cited_by_count":2,"area":null},{"id":"2302.00814","title":"Stochastic Contextual Bandits with Long Horizon Rewards","created":"2023-02-02","cited_by_count":1,"area":null},{"id":"2410.12086","title":"Comparative Performance of Collaborative Bandit Algorithms: Effect of Sparsity and Exploration Intensity","created":"2024-10-15","cited_by_count":1,"area":null},{"id":"2510.00309","title":"Lipschitz Bandits with Stochastic Delayed Feedback","created":"2025-09-30","cited_by_count":1,"area":null},{"id":"2603.13742","title":"Few Batches or Little Memory, But Not Both: Simultaneous Space and Adaptivity Constraints in Stochastic Bandits","created":"2026-03-14","cited_by_count":1,"area":null},{"id":"2605.30976","title":"Batched Stochastic Linear Bandits with 1-Bit Communication Constraints","created":"2026-05-29","cited_by_count":1,"area":null},{"id":"2609.05820","title":"Online Learning with LLM Experts from Limited Feedback","created":"2026-09-05","cited_by_count":1,"area":null},{"id":"2106.02855","title":"Multi-armed Bandit Algorithms on System-on-Chip: Go Frequentist or Bayesian?","created":"2021-06-05","cited_by_count":0,"area":null},{"id":"2303.00620","title":"Multi-Armed Bandits with Generalized Temporally-Partitioned Rewards","created":"2023-03-01","cited_by_count":0,"area":null},{"id":"2405.11417","title":"Budgeted Recommendation with Delayed Feedback","created":"2024-05-19","cited_by_count":0,"area":null},{"id":"2502.07397","title":"Linear Bandits beyond Inner Product Spaces, the case of Bandit Optimal Transport","created":"2025-02-11","cited_by_count":0,"area":null},{"id":"2505.20017","title":"Linear Bandits with Non-i.i.d. Noise","created":"2025-05-26","cited_by_count":0,"area":null},{"id":"2510.04421","title":"Learning Survival Models with Right-Censored Reporting Delays","created":"2025-10-06","cited_by_count":0,"area":null},{"id":"2602.06276","title":"Statistical Learning from Attribution Sets","created":"2026-02-06","cited_by_count":0,"area":null},{"id":"2603.03480","title":"Minimax Optimal Strategy for Delayed Observations in Online Reinforcement Learning","created":"2026-03-03","cited_by_count":0,"area":"deeprl"},{"id":"2605.01752","title":"Robust Linear Dueling Bandits with Post-serving Context under Unknown Delays and Adversarial Corruptions","created":"2026-05-03","cited_by_count":0,"area":null},{"id":"2606.16656","title":"Near-Optimal Stochastic Linear Bandits with Delay","created":"2026-06-15","cited_by_count":0,"area":null},{"id":"2608.15036","title":"Lipschitz Bandits with Arbitrary Feedback Delays","created":"2026-08-15","cited_by_count":0,"area":null},{"id":"2609.31047","title":"DynBranch: Speculative Subgraph Reuse for Dynamic Agentic LLM Serving","created":"2026-09-25","cited_by_count":0,"area":"agents"}],"next_cursor":null}