Imagen de Portada

Parameter-free Dynamic Regret: Time-varying Movement Costs, Delayed Feedback, and Memory

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Qiu, Hao, Jacobsen, Andrew, Esposito, Emmanuel, Zhang, Mengxiao
Formato:	Preprint
Publicado:	2026
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Exploiting Curvature in Online Convex Optimization with Delayed Feedback
por: Qiu, Hao, et al.
Publicado: (2025)

Decentralized Online Convex Optimization with Unknown Feedback Delays
por: Qiu, Hao, et al.
Publicado: (2026)

Parameter-Free Dynamic Regret for Unconstrained Linear Bandits
por: Rumi, Alberto, et al.
Publicado: (2026)

Near-Optimal Regret for Distributed Adversarial Bandits: A Black-Box Approach
por: Qiu, Hao, et al.
Publicado: (2026)

Dynamic Regret Reduces to Kernelized Static Regret
por: Jacobsen, Andrew, et al.
Publicado: (2025)

An Equivalence Between Static and Dynamic Regret Minimization
por: Jacobsen, Andrew, et al.
Publicado: (2024)

Parameter-free Mirror Descent
por: Jacobsen, Andrew, et al.
Publicado: (2022)

Improved Regret for Bandit Convex Optimization with Delayed Feedback
por: Wan, Yuanyu, et al.
Publicado: (2024)

Alternating Regret for Online Convex Optimization
por: Hait, Soumita, et al.
Publicado: (2025)

Autobidders with Budget and ROI Constraints: Efficiency, Regret, and Pacing Dynamics
por: Lucier, Brendan, et al.
Publicado: (2023)

Improved Best-of-Both-Worlds Regret for Bandits with Delayed Feedback
por: Schlisselberg, Ofir, et al.
Publicado: (2025)

Improved Regret Bounds for Bandits with Expert Advice
por: Cesa-Bianchi, Nicolò, et al.
Publicado: (2024)

Contextual Linear Bandits with Delay as Payoff
por: Zhang, Mengxiao, et al.
Publicado: (2025)

Comparator-Adaptive $Φ$-Regret: Improved Bounds, Simpler Algorithms, and Applications to Games
por: Hait, Soumita, et al.
Publicado: (2025)

Gradient-Variation Regret Bounds for Unconstrained Online Learning
por: Zhao, Yuheng, et al.
Publicado: (2026)

Regret Bounds for Adversarial Contextual Bandits with General Function Approximation and Delayed Feedback
por: Levy, Orin, et al.
Publicado: (2025)

Efficient Contextual Bandits with Uninformed Feedback Graphs
por: Zhang, Mengxiao, et al.
Publicado: (2024)

Interaction-Grounded Learning for Contextual Markov Decision Processes with Personalized Feedback
por: Zhang, Mengxiao, et al.
Publicado: (2026)

No-Regret Learning for Fair Multi-Agent Social Welfare Optimization
por: Zhang, Mengxiao, et al.
Publicado: (2024)

Near-Optimal Regret in Adversarial Kernel Bandits
por: Zhang, Yu-Jie, et al.
Publicado: (2026)

Online Linear Regression in Dynamic Environments via Discounting
por: Jacobsen, Andrew, et al.
Publicado: (2024)

On the Minimax Regret in Online Ranking with Top-k Feedback
por: Zhang, Mingyuan, et al.
Publicado: (2023)

Asynchronous Distributed Optimization with Delay-free Parameters
por: Wu, Xuyang, et al.
Publicado: (2023)

Near-Optimal Last-Iterate Convergence for Zero-Sum Games with Bandit Feedback and Opponent Actions
por: Hait, Soumita, et al.
Publicado: (2026)

Bayesian Optimization for Unknown Cost-Varying Variable Subsets with No-Regret Costs
por: Hoang, Vu Viet, et al.
Publicado: (2024)

Information Capacity Regret Bounds for Bandits with Mediator Feedback
por: Eldowa, Khaled, et al.
Publicado: (2024)

Contextual Multinomial Logit Bandits with General Value Functions
por: Zhang, Mengxiao, et al.
Publicado: (2024)

Near-Optimal Regret in Linear MDPs with Aggregate Bandit Feedback
por: Cassel, Asaf, et al.
Publicado: (2024)

Budgeted Recommendation with Delayed Feedback
por: Liu, Kweiguu, et al.
Publicado: (2024)

Improved Dynamic Regret for Online Frank-Wolfe
por: Wan, Yuanyu, et al.
Publicado: (2023)

Capacity-Constrained Online Learning with Delays: Scheduling Frameworks and Regret Trade-offs
por: Ryabchenko, Alexander, et al.
Publicado: (2025)

Online Nonsubmodular Optimization with Delayed Feedback in the Bandit Setting
por: Yang, Sifan, et al.
Publicado: (2025)

Learning on the Edge: Online Learning with Stochastic Feedback Graphs
por: Esposito, Emmanuel, et al.
Publicado: (2022)

Regret-Optimal Q-Learning with Low Cost for Single-Agent and Federated Reinforcement Learning
por: Zhang, Haochen, et al.
Publicado: (2025)

Bayesian Optimization from Human Feedback: Near-Optimal Regret Bounds
por: Kayal, Aya, et al.
Publicado: (2025)

Stochastic Online Instrumental Variable Regression: Regrets for Endogeneity and Bandit Feedback
por: Della Vecchia, Riccardo, et al.
Publicado: (2023)

Distributed Online Bandit Nonconvex Optimization with One-Point Residual Feedback via Dynamic Regret
por: Hua, Youqing, et al.
Publicado: (2024)

Lipschitz Bandits with Stochastic Delayed Feedback
por: Liu, Zhongxuan, et al.
Publicado: (2025)

Delayed Feedback Modeling with Influence Functions
por: Ding, Chenlu, et al.
Publicado: (2025)

Federated Q-Learning: Linear Regret Speedup with Low Communication Cost
por: Zheng, Zhong, et al.
Publicado: (2023)