Copertina

Tight Gap-Dependent Memory-Regret Trade-Off for Single-Pass Streaming Stochastic Multi-Armed Bandits

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Ye, Zichun, Zhang, Chihao, Zhao, Jiahao
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning Data Structures and Algorithms
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Understanding Memory-Regret Trade-Off for Streaming Stochastic Multi-Armed Bandits
di: He, Yuchen, et al.
Pubblicazione: (2024)

Unlearning Offline Stochastic Multi-Armed Bandits
di: Ye, Zichun, et al.
Pubblicazione: (2026)

Near-Optimal Regret for Efficient Stochastic Combinatorial Semi-Bandits
di: Ye, Zichun, et al.
Pubblicazione: (2025)

Stochastic Multi-Objective Multi-Armed Bandits: Regret Definition and Algorithm
di: Davoodi, Mansoor, et al.
Pubblicazione: (2025)

Nearly Tight Bounds for Exploration in Streaming Multi-armed Bandits with Known Optimality Gap
di: Karpov, Nikolai, et al.
Pubblicazione: (2025)

Adversarial Attacks on Combinatorial Multi-Armed Bandits
di: Balasubramanian, Rishab, et al.
Pubblicazione: (2023)

Introduction to Multi-Armed Bandits
di: Slivkins, Aleksandrs
Pubblicazione: (2019)

Nearly-tight Approximation Guarantees for the Improving Multi-Armed Bandits Problem
di: Blum, Avrim, et al.
Pubblicazione: (2024)

On the query complexity of sampling from non-log-concave distributions
di: He, Yuchen, et al.
Pubblicazione: (2025)

No-Regret M${}^{\natural}$-Concave Function Maximization: Stochastic Bandit Algorithms and Hardness of Adversarial Full-Information Setting
di: Oki, Taihei, et al.
Pubblicazione: (2024)

On the Problem of Best Arm Retention
di: Chen, Houshuang, et al.
Pubblicazione: (2025)

Stochastic $k$-Submodular Bandits with Full Bandit Feedback
di: Nie, Guanyu, et al.
Pubblicazione: (2024)

A Single-Sample Polylogarithmic Regret Bound for Nonstationary Online Linear Programming
di: Xu, Haoran, et al.
Pubblicazione: (2026)

Stochastic Bandits with ReLU Neural Networks
di: Xu, Kan, et al.
Pubblicazione: (2024)

Semi-Bandit Learning for Monotone Stochastic Optimization
di: Agarwal, Arpit, et al.
Pubblicazione: (2023)

The Best Arm Evades: Near-optimal Multi-pass Streaming Lower Bounds for Pure Exploration in Multi-armed Bandits
di: Assadi, Sepehr, et al.
Pubblicazione: (2023)

Improved sampling algorithms and functional inequalities for non-log-concave distributions
di: He, Yuchen, et al.
Pubblicazione: (2025)

$O(\sqrt{T})$ Static Regret and Instance Dependent Constraint Violation for Constrained Online Convex Optimization
di: Vaze, Rahul, et al.
Pubblicazione: (2025)

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities
di: Su, Yuexin, et al.
Pubblicazione: (2025)

Stochastic Submodular Bandits with Delayed Composite Anonymous Bandit Feedback
di: Pedramfar, Mohammad, et al.
Pubblicazione: (2023)

Convergence of a L2 regularized Policy Gradient Algorithm for the Multi Armed Bandit
di: Anita, Stefana, et al.
Pubblicazione: (2024)

Tight Bounds for Learning Polyhedra with a Margin
di: Patel, Shyamal, et al.
Pubblicazione: (2026)

Near-optimal Swap Regret Minimization for Convex Losses
di: Hu, Lunjia, et al.
Pubblicazione: (2026)

Tight Bounds for Answering Adaptively Chosen Concentrated Queries
di: Rapoport, Emma, et al.
Pubblicazione: (2025)

Tight Differentially Private PCA via Matrix Coherence
di: d'Orsi, Tommaso, et al.
Pubblicazione: (2025)

Towards Optimal Differentially Private Regret Bounds in Linear MDPs
di: Sahu, Sharan
Pubblicazione: (2025)

Efficient, Low-Regret, Online Reinforcement Learning for Linear MDPs
di: John, Philips George, et al.
Pubblicazione: (2024)

Linear Submodular Maximization with Bandit Feedback
di: Chen, Wenjing, et al.
Pubblicazione: (2024)

High-dimensional Linear Bandits with Knapsacks
di: Ma, Wanteng, et al.
Pubblicazione: (2023)

Improved Regret in Stochastic Decision-Theoretic Online Learning under Differential Privacy
di: Wu, Ruihan, et al.
Pubblicazione: (2025)

Online Algorithms for Repeated Optimal Stopping: Balancing Baseline Guarantees and Regret
di: Harada, Tsubasa, et al.
Pubblicazione: (2025)

Minimizing Cost Rather Than Maximizing Reward in Restless Multi-Armed Bandits
di: Witter, R. Teal, et al.
Pubblicazione: (2024)

MNL-Bandit with Knapsacks: a near-optimal algorithm
di: Aznag, Abdellah, et al.
Pubblicazione: (2021)

From Average Sensitivity to Small-Loss Regret Bounds under Random-Order Model
di: Sakaue, Shinsaku, et al.
Pubblicazione: (2026)

Optimal Scalarizations for Sublinear Hypervolume Regret
di: Zhang, Qiuyi
Pubblicazione: (2023)

A Tight Lower Bound for the Approximation Guarantee of Higher-Order Singular Value Decomposition
di: Fahrbach, Matthew, et al.
Pubblicazione: (2025)

Single-Pass Streaming CSPs via Two-Tier Sampling
di: Azarmehr, Amir, et al.
Pubblicazione: (2026)

Space Complexity of Minimum Cut Problems in Single-Pass Streams
di: Ding, Matthew, et al.
Pubblicazione: (2024)

The Cost of Compression: Tight Quadratic Black-Box Attacks on Sketches for $\ell_2$ Norm Estimation
di: Ahmadian, Sara, et al.
Pubblicazione: (2025)

Greedy Algorithm for Structured Bandits: A Sharp Characterization of Asymptotic Success / Failure
di: Slivkins, Aleksandrs, et al.
Pubblicazione: (2025)