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A Closer Look at Small-loss Bounds for Bandits with Graph Feedback
v1v2 (latest)

A Closer Look at Small-loss Bounds for Bandits with Graph Feedback

Annual Conference Computational Learning Theory (COLT), 2020
2 February 2020
Chung-Wei Lee
Haipeng Luo
Mengxiao Zhang
ArXiv (abs)PDFHTML

Papers citing "A Closer Look at Small-loss Bounds for Bandits with Graph Feedback"

22 / 22 papers shown
Data-Dependent Regret Bounds for Constrained MABs
Data-Dependent Regret Bounds for Constrained MABs
Gianmarco Genalti
Francesco Emanuele Stradi
Matteo Castiglioni
A. Marchesi
N. Gatti
372
0
0
26 May 2025
Online Two-Sided Markets: Many Buyers Enhance Learning
Anna Lunghi
Matteo Castiglioni
A. Marchesi
230
0
0
03 Mar 2025
uniINF: Best-of-Both-Worlds Algorithm for Parameter-Free Heavy-Tailed MABs
uniINF: Best-of-Both-Worlds Algorithm for Parameter-Free Heavy-Tailed MABsInternational Conference on Learning Representations (ICLR), 2024
Yu Chen
Jiatai Huang
Yan Dai
Longbo Huang
358
5
0
04 Oct 2024
Graph Neural Thompson Sampling
Graph Neural Thompson Sampling
Shuang Wu
Arash A. Amini
354
1
0
15 Jun 2024
Incentive-compatible Bandits: Importance Weighting No More
Incentive-compatible Bandits: Importance Weighting No More
Julian Zimmert
T. V. Marinov
192
0
0
10 May 2024
Efficient Contextual Bandits with Uninformed Feedback Graphs
Efficient Contextual Bandits with Uninformed Feedback Graphs
Mengxiao Zhang
Yuheng Zhang
Haipeng Luo
Paul Mineiro
182
4
0
12 Feb 2024
Online Network Source Optimization with Graph-Kernel MAB
Online Network Source Optimization with Graph-Kernel MAB
Laura Toni
P. Frossard
317
1
0
07 Jul 2023
Nearly Optimal Algorithms with Sublinear Computational Complexity for
  Online Kernel Regression
Nearly Optimal Algorithms with Sublinear Computational Complexity for Online Kernel RegressionInternational Conference on Machine Learning (ICML), 2023
Junfan Li
Shizhong Liao
191
1
0
14 Jun 2023
Stability-penalty-adaptive follow-the-regularized-leader: Sparsity,
  game-dependency, and best-of-both-worlds
Stability-penalty-adaptive follow-the-regularized-leader: Sparsity, game-dependency, and best-of-both-worldsNeural Information Processing Systems (NeurIPS), 2023
Taira Tsuchiya
Shinji Ito
Junya Honda
219
13
0
26 May 2023
Practical Contextual Bandits with Feedback Graphs
Practical Contextual Bandits with Feedback GraphsNeural Information Processing Systems (NeurIPS), 2023
Mengxiao Zhang
Yuheng Zhang
Olga Vrousgou
Haipeng Luo
Paul Mineiro
318
9
0
17 Feb 2023
Improved High-Probability Regret for Adversarial Bandits with
  Time-Varying Feedback Graphs
Improved High-Probability Regret for Adversarial Bandits with Time-Varying Feedback GraphsInternational Conference on Algorithmic Learning Theory (ALT), 2022
Haipeng Luo
Hanghang Tong
Mengxiao Zhang
Yuheng Zhang
201
5
0
04 Oct 2022
Regret Minimization and Convergence to Equilibria in General-sum Markov Games
Regret Minimization and Convergence to Equilibria in General-sum Markov GamesInternational Conference on Machine Learning (ICML), 2022
Liad Erez
Tal Lancewicki
Uri Sherman
Tomer Koren
Yishay Mansour
319
33
0
28 Jul 2022
Stochastic Online Learning with Feedback Graphs: Finite-Time and
  Asymptotic Optimality
Stochastic Online Learning with Feedback Graphs: Finite-Time and Asymptotic OptimalityNeural Information Processing Systems (NeurIPS), 2022
T. V. Marinov
M. Mohri
Julian Zimmert
196
6
0
20 Jun 2022
Corralling a Larger Band of Bandits: A Case Study on Switching Regret
  for Linear Bandits
Corralling a Larger Band of Bandits: A Case Study on Switching Regret for Linear BanditsAnnual Conference Computational Learning Theory (COLT), 2022
Haipeng Luo
Mengxiao Zhang
Peng Zhao
Zhi Zhou
205
20
0
12 Feb 2022
Adaptivity and Non-stationarity: Problem-dependent Dynamic Regret for
  Online Convex Optimization
Adaptivity and Non-stationarity: Problem-dependent Dynamic Regret for Online Convex OptimizationJournal of machine learning research (JMLR), 2021
Peng Zhao
Yu Zhang
Lijun Zhang
Zhi Zhou
342
77
0
29 Dec 2021
Best-of-All-Worlds Bounds for Online Learning with Feedback Graphs
Best-of-All-Worlds Bounds for Online Learning with Feedback Graphs
Liad Erez
Tomer Koren
136
5
0
20 Jul 2021
The best of both worlds: stochastic and adversarial episodic MDPs with
  unknown transition
The best of both worlds: stochastic and adversarial episodic MDPs with unknown transitionNeural Information Processing Systems (NeurIPS), 2021
Tiancheng Jin
Longbo Huang
Haipeng Luo
225
45
0
08 Jun 2021
Understanding Bandits with Graph Feedback
Understanding Bandits with Graph FeedbackNeural Information Processing Systems (NeurIPS), 2021
Houshuang Chen
Zengfeng Huang
Shuai Li
Chihao Zhang
116
12
0
29 May 2021
Adversarial Linear Contextual Bandits with Graph-Structured Side
  Observations
Adversarial Linear Contextual Bandits with Graph-Structured Side ObservationsAAAI Conference on Artificial Intelligence (AAAI), 2020
Lingda Wang
Bingcong Li
Huozhi Zhou
G. Giannakis
Lav Varshney
Zhizhen Zhao
255
9
0
10 Dec 2020
Minimax Regret for Stochastic Shortest Path with Adversarial Costs and
  Known Transition
Minimax Regret for Stochastic Shortest Path with Adversarial Costs and Known Transition
Liyu Chen
Haipeng Luo
Chen-Yu Wei
496
35
0
07 Dec 2020
Bias no more: high-probability data-dependent regret bounds for
  adversarial bandits and MDPs
Bias no more: high-probability data-dependent regret bounds for adversarial bandits and MDPsNeural Information Processing Systems (NeurIPS), 2020
Chung-Wei Lee
Haipeng Luo
Chen-Yu Wei
Mengxiao Zhang
351
59
0
14 Jun 2020
Simultaneously Learning Stochastic and Adversarial Episodic MDPs with
  Known Transition
Simultaneously Learning Stochastic and Adversarial Episodic MDPs with Known TransitionNeural Information Processing Systems (NeurIPS), 2020
Tiancheng Jin
Haipeng Luo
284
60
0
10 Jun 2020
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