Unlearning Offline Stochastic Multi-Armed Bandits
Fuente:
arXiv
Guardado en:
| Autores principales: | Ye, Zichun, Wang, Runqi, Wang, Xuchuang, Liu, Xutong, Li, Shuai, Hajiesmaili, Mohammad |
|---|---|
| Formato: | Preprint |
| Publicado: |
2026
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Near-Optimal Regret for Efficient Stochastic Combinatorial Semi-Bandits
por: Ye, Zichun, et al.
Publicado: (2025)
por: Ye, Zichun, et al.
Publicado: (2025)
Understanding Memory-Regret Trade-Off for Streaming Stochastic Multi-Armed Bandits
por: He, Yuchen, et al.
Publicado: (2024)
por: He, Yuchen, et al.
Publicado: (2024)
Tight Gap-Dependent Memory-Regret Trade-Off for Single-Pass Streaming Stochastic Multi-Armed Bandits
por: Ye, Zichun, et al.
Publicado: (2025)
por: Ye, Zichun, et al.
Publicado: (2025)
Stochastic Multi-Objective Multi-Armed Bandits: Regret Definition and Algorithm
por: Davoodi, Mansoor, et al.
Publicado: (2025)
por: Davoodi, Mansoor, et al.
Publicado: (2025)
Adversarial Attacks on Combinatorial Multi-Armed Bandits
por: Balasubramanian, Rishab, et al.
Publicado: (2023)
por: Balasubramanian, Rishab, et al.
Publicado: (2023)
Introduction to Multi-Armed Bandits
por: Slivkins, Aleksandrs
Publicado: (2019)
por: Slivkins, Aleksandrs
Publicado: (2019)
Nearly-tight Approximation Guarantees for the Improving Multi-Armed Bandits Problem
por: Blum, Avrim, et al.
Publicado: (2024)
por: Blum, Avrim, et al.
Publicado: (2024)
Signal-Aware Workload Shifting Algorithms with Uncertainty-Quantified Predictors
por: Johnson, Ezra, et al.
Publicado: (2025)
por: Johnson, Ezra, et al.
Publicado: (2025)
Robust Learning-Augmented Dictionaries
por: Zeynali, Ali, et al.
Publicado: (2024)
por: Zeynali, Ali, et al.
Publicado: (2024)
Stochastic $k$-Submodular Bandits with Full Bandit Feedback
por: Nie, Guanyu, et al.
Publicado: (2024)
por: Nie, Guanyu, et al.
Publicado: (2024)
Stochastic Submodular Bandits with Delayed Composite Anonymous Bandit Feedback
por: Pedramfar, Mohammad, et al.
Publicado: (2023)
por: Pedramfar, Mohammad, et al.
Publicado: (2023)
Online Search with Predictions: Pareto-optimal Algorithm and its Applications in Energy Markets
por: Lee, Russell, et al.
Publicado: (2022)
por: Lee, Russell, et al.
Publicado: (2022)
Stochastic Bandits with ReLU Neural Networks
por: Xu, Kan, et al.
Publicado: (2024)
por: Xu, Kan, et al.
Publicado: (2024)
Semi-Bandit Learning for Monotone Stochastic Optimization
por: Agarwal, Arpit, et al.
Publicado: (2023)
por: Agarwal, Arpit, et al.
Publicado: (2023)
Online Algorithms with Uncertainty-Quantified Predictions
por: Sun, Bo, et al.
Publicado: (2023)
por: Sun, Bo, et al.
Publicado: (2023)
Nearly Tight Bounds for Exploration in Streaming Multi-armed Bandits with Known Optimality Gap
por: Karpov, Nikolai, et al.
Publicado: (2025)
por: Karpov, Nikolai, et al.
Publicado: (2025)
The Best Arm Evades: Near-optimal Multi-pass Streaming Lower Bounds for Pure Exploration in Multi-armed Bandits
por: Assadi, Sepehr, et al.
Publicado: (2023)
por: Assadi, Sepehr, et al.
Publicado: (2023)
Online Conversion with Switching Costs: Robust and Learning-Augmented Algorithms
por: Lechowicz, Adam, et al.
Publicado: (2023)
por: Lechowicz, Adam, et al.
Publicado: (2023)
Chasing Convex Functions with Long-term Constraints
por: Lechowicz, Adam, et al.
Publicado: (2024)
por: Lechowicz, Adam, et al.
Publicado: (2024)
Convergence of a L2 regularized Policy Gradient Algorithm for the Multi Armed Bandit
por: Anita, Stefana, et al.
Publicado: (2024)
por: Anita, Stefana, et al.
Publicado: (2024)
No-Regret M${}^{\natural}$-Concave Function Maximization: Stochastic Bandit Algorithms and Hardness of Adversarial Full-Information Setting
por: Oki, Taihei, et al.
Publicado: (2024)
por: Oki, Taihei, et al.
Publicado: (2024)
Online Smoothed Demand Management
por: Lechowicz, Adam, et al.
Publicado: (2025)
por: Lechowicz, Adam, et al.
Publicado: (2025)
Time Fairness in Online Knapsack Problems
por: Lechowicz, Adam, et al.
Publicado: (2023)
por: Lechowicz, Adam, et al.
Publicado: (2023)
Stochastic Matching via Local Sparsification
por: Ahmadian, Sara, et al.
Publicado: (2026)
por: Ahmadian, Sara, et al.
Publicado: (2026)
Protecting the Undeleted in Machine Unlearning
por: Cohen, Aloni, et al.
Publicado: (2026)
por: Cohen, Aloni, et al.
Publicado: (2026)
Linear Submodular Maximization with Bandit Feedback
por: Chen, Wenjing, et al.
Publicado: (2024)
por: Chen, Wenjing, et al.
Publicado: (2024)
High-dimensional Linear Bandits with Knapsacks
por: Ma, Wanteng, et al.
Publicado: (2023)
por: Ma, Wanteng, et al.
Publicado: (2023)
Minimizing Cost Rather Than Maximizing Reward in Restless Multi-Armed Bandits
por: Witter, R. Teal, et al.
Publicado: (2024)
por: Witter, R. Teal, et al.
Publicado: (2024)
MNL-Bandit with Knapsacks: a near-optimal algorithm
por: Aznag, Abdellah, et al.
Publicado: (2021)
por: Aznag, Abdellah, et al.
Publicado: (2021)
Greedy Algorithm for Structured Bandits: A Sharp Characterization of Asymptotic Success / Failure
por: Slivkins, Aleksandrs, et al.
Publicado: (2025)
por: Slivkins, Aleksandrs, et al.
Publicado: (2025)
Stochastic Bandits Robust to Adversarial Attacks
por: Wang, Xuchuang, et al.
Publicado: (2024)
por: Wang, Xuchuang, et al.
Publicado: (2024)
Replicable Uniformity Testing
por: Liu, Sihan, et al.
Publicado: (2024)
por: Liu, Sihan, et al.
Publicado: (2024)
Heterogeneous Multi-agent Multi-armed Bandits on Stochastic Block Models
por: Xu, Mengfan, et al.
Publicado: (2025)
por: Xu, Mengfan, et al.
Publicado: (2025)
Learning on the Edge: Online Learning with Stochastic Feedback Graphs
por: Esposito, Emmanuel, et al.
Publicado: (2022)
por: Esposito, Emmanuel, et al.
Publicado: (2022)
Differential Private Stochastic Optimization with Heavy-tailed Data: Towards Optimal Rates
por: Zhao, Puning, et al.
Publicado: (2024)
por: Zhao, Puning, et al.
Publicado: (2024)
Towards counterfactual fairness through auxiliary variables
por: Tian, Bowei, et al.
Publicado: (2024)
por: Tian, Bowei, et al.
Publicado: (2024)
Replicable Composition
por: Banihashem, Kiarash, et al.
Publicado: (2026)
por: Banihashem, Kiarash, et al.
Publicado: (2026)
Learned LSM-trees: Two Approaches Using Learned Bloom Filters
por: Fidalgo, Nicholas, et al.
Publicado: (2025)
por: Fidalgo, Nicholas, et al.
Publicado: (2025)
Learning-Augmented Competitive Algorithms for Spatiotemporal Online Allocation with Deadline Constraints
por: Lechowicz, Adam, et al.
Publicado: (2024)
por: Lechowicz, Adam, et al.
Publicado: (2024)
Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities
por: Su, Yuexin, et al.
Publicado: (2025)
por: Su, Yuexin, et al.
Publicado: (2025)
Ejemplares similares
-
Near-Optimal Regret for Efficient Stochastic Combinatorial Semi-Bandits
por: Ye, Zichun, et al.
Publicado: (2025) -
Understanding Memory-Regret Trade-Off for Streaming Stochastic Multi-Armed Bandits
por: He, Yuchen, et al.
Publicado: (2024) -
Tight Gap-Dependent Memory-Regret Trade-Off for Single-Pass Streaming Stochastic Multi-Armed Bandits
por: Ye, Zichun, et al.
Publicado: (2025) -
Stochastic Multi-Objective Multi-Armed Bandits: Regret Definition and Algorithm
por: Davoodi, Mansoor, et al.
Publicado: (2025) -
Adversarial Attacks on Combinatorial Multi-Armed Bandits
por: Balasubramanian, Rishab, et al.
Publicado: (2023)