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1612.06246
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Corralling a Band of Bandit Algorithms
Annual Conference Computational Learning Theory (COLT), 2016
19 December 2016
Alekh Agarwal
Haipeng Luo
Behnam Neyshabur
Robert Schapire
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Papers citing
"Corralling a Band of Bandit Algorithms"
50 / 121 papers shown
Improved Training Mechanism for Reinforcement Learning via Online Model Selection
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A Polynomial-time Algorithm for Online Sparse Linear Regression with Improved Regret Bound under Weaker Conditions
Annual Conference Computational Learning Theory (COLT), 2025
Junfan Li
Shizhong Liao
Zenglin Xu
L. Nie
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31 Oct 2025
UCB-type Algorithm for Budget-Constrained Expert Learning
Ilgam Latypov
A. Suvorikova
Alexey Kroshnin
Alexander Gasnikov
Yuriy Dorn
96
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Data-Dependent Regret Bounds for Constrained MABs
Gianmarco Genalti
Francesco Emanuele Stradi
Matteo Castiglioni
A. Marchesi
N. Gatti
372
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26 May 2025
Sparse Nonparametric Contextual Bandits
Hamish Flynn
Julia Olkhovskaya
Paul Rognon-Vael
349
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20 Mar 2025
Offline-to-online hyperparameter transfer for stochastic bandits
AAAI Conference on Artificial Intelligence (AAAI), 2025
Dravyansh Sharma
Arun Sai Suggala
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300
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06 Jan 2025
A Model Selection Approach for Corruption Robust Reinforcement Learning
International Conference on Algorithmic Learning Theory (ALT), 2021
Chen-Yu Wei
Christoph Dann
Julian Zimmert
290
49
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31 Dec 2024
Adaptive Resource Allocation for Virtualized Base Stations in O-RAN with Online Learning
IEEE Transactions on Communications (IEEE Trans. Commun.), 2023
Michail Kalntis
Georgios Iosifidis
Fernando A. Kuipers
152
11
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31 Dec 2024
Model Selection for Average Reward RL with Application to Utility Maximization in Repeated Games
Alireza Masoumian
James R. Wright
434
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09 Nov 2024
Bayesian Optimisation with Unknown Hyperparameters: Regret Bounds Logarithmically Closer to Optimal
Neural Information Processing Systems (NeurIPS), 2024
Juliusz Ziomek
Masaki Adachi
Michael A. Osborne
423
4
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14 Oct 2024
Stochastic Bandits Robust to Adversarial Attacks
Xuchuang Wang
Jinhang Zuo
Xutong Liu
John C. S. Lui
Mohammad Hajiesmaili
AAML
141
1
0
16 Aug 2024
Learning Rate-Free Reinforcement Learning: A Case for Model Selection with Non-Stationary Objectives
Aida Afshar
Aldo Pacchiano
215
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07 Aug 2024
Causal Bandits: The Pareto Optimal Frontier of Adaptivity, a Reduction to Linear Bandits, and Limitations around Unknown Marginals
Ziyi Liu
Idan Attias
Daniel M. Roy
CML
199
2
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01 Jul 2024
Efficient Sequential Decision Making with Large Language Models
Dingyang Chen
Qi Zhang
Yinglun Zhu
LRM
419
9
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17 Jun 2024
No-Regret Learning for Fair Multi-Agent Social Welfare Optimization
Mengxiao Zhang
Ramiro Deo-Campo Vuong
Haipeng Luo
212
5
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31 May 2024
Symmetric Linear Bandits with Hidden Symmetry
Nam-Phuong Tran
T. Ta
Debmalya Mandal
Long Tran-Thanh
335
1
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22 May 2024
Incentive-compatible Bandits: Importance Weighting No More
Julian Zimmert
T. V. Marinov
208
0
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10 May 2024
Online Bandits with (Biased) Offline Data: Adaptive Learning under Distribution Mismatch
International Conference on Machine Learning (ICML), 2024
Wang Chi Cheung
Lixing Lyu
OffRL
428
12
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04 May 2024
The SMART approach to instance-optimal online learning
Siddhartha Banerjee
Alankrita Bhatt
Chao Yu
185
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27 Feb 2024
Model Assessment and Selection under Temporal Distribution Shift
Elise Han
Chengpiao Huang
Kaizheng Wang
OOD
294
6
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13 Feb 2024
Experiment Planning with Function Approximation
Neural Information Processing Systems (NeurIPS), 2024
Aldo Pacchiano
Jonathan Lee
Emma Brunskill
OffRL
190
4
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10 Jan 2024
Best-of-Both-Worlds Algorithms for Linear Contextual Bandits
Yuko Kuroki
Alberto Rumi
Taira Tsuchiya
Fabio Vitale
Nicolò Cesa-Bianchi
292
11
0
24 Dec 2023
An Improved Relaxation for Oracle-Efficient Adversarial Contextual Bandits
Neural Information Processing Systems (NeurIPS), 2023
Kiarash Banihashem
Mohammadtaghi Hajiaghayi
Suho Shin
Max Springer
268
1
0
29 Oct 2023
Bypassing the Simulator: Near-Optimal Adversarial Linear Contextual Bandits
Neural Information Processing Systems (NeurIPS), 2023
Haolin Liu
Chen-Yu Wei
Julian Zimmert
245
11
0
02 Sep 2023
Anytime Model Selection in Linear Bandits
Neural Information Processing Systems (NeurIPS), 2023
Parnian Kassraie
N. Emmenegger
Andreas Krause
Aldo Pacchiano
306
7
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24 Jul 2023
Data-Driven Online Model Selection With Regret Guarantees
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Aldo Pacchiano
Christoph Dann
Claudio Gentile
OffRL
336
9
0
05 Jun 2023
Adaptation to Misspecified Kernel Regularity in Kernelised Bandits
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Yusha Liu
Aarti Singh
248
3
0
26 Apr 2023
Improved Regret Bounds for Online Kernel Selection under Bandit Feedback
Junfan Li
Shizhong Liao
134
1
0
09 Mar 2023
A Blackbox Approach to Best of Both Worlds in Bandits and Beyond
Annual Conference Computational Learning Theory (COLT), 2023
Christoph Dann
Chen-Yu Wei
Julian Zimmert
231
29
0
20 Feb 2023
Estimating Optimal Policy Value in General Linear Contextual Bandits
Jonathan Lee
Weihao Kong
Aldo Pacchiano
Vidya Muthukumar
Emma Brunskill
197
0
0
19 Feb 2023
Online Continuous Hyperparameter Optimization for Generalized Linear Contextual Bandits
Yue Kang
Cho-Jui Hsieh
T. C. Lee
290
2
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18 Feb 2023
Leveraging User-Triggered Supervision in Contextual Bandits
Alekh Agarwal
Claudio Gentile
T. V. Marinov
173
0
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07 Feb 2023
Banker Online Mirror Descent: A Universal Approach for Delayed Online Bandit Learning
International Conference on Machine Learning (ICML), 2023
Jiatai Huang
Yan Dai
Longbo Huang
281
7
0
25 Jan 2023
Stochastic Rising Bandits
International Conference on Machine Learning (ICML), 2022
Alberto Maria Metelli
F. Trovò
Matteo Pirola
Marcello Restelli
165
18
0
07 Dec 2022
Oracle Inequalities for Model Selection in Offline Reinforcement Learning
Neural Information Processing Systems (NeurIPS), 2022
Jonathan Lee
George Tucker
Ofir Nachum
Bo Dai
Emma Brunskill
OffRL
336
14
0
03 Nov 2022
Lifelong Bandit Optimization: No Prior and No Regret
Conference on Uncertainty in Artificial Intelligence (UAI), 2022
Felix Schur
Parnian Kassraie
Jonas Rothfuss
Andreas Krause
324
3
0
27 Oct 2022
One Arrow, Two Kills: An Unified Framework for Achieving Optimal Regret Guarantees in Sleeping Bandits
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Pierre Gaillard
Aadirupa Saha
Soham Dan
191
3
0
26 Oct 2022
Eigen Memory Trees
Mark Rucker
Jordan T. Ash
John Langford
Paul Mineiro
Ida Momennejad
179
0
0
25 Oct 2022
Conditionally Risk-Averse Contextual Bandits
Mónika Farsang
Paul Mineiro
Wangda Zhang
248
2
0
24 Oct 2022
Scalable Representation Learning in Linear Contextual Bandits with Constant Regret Guarantees
Neural Information Processing Systems (NeurIPS), 2022
Andrea Tirinzoni
Matteo Papini
Ahmed Touati
A. Lazaric
Matteo Pirotta
253
6
0
24 Oct 2022
Unpacking Reward Shaping: Understanding the Benefits of Reward Engineering on Sample Complexity
Neural Information Processing Systems (NeurIPS), 2022
Abhishek Gupta
Aldo Pacchiano
Yuexiang Zhai
Sham Kakade
Sergey Levine
OffRL
219
94
0
18 Oct 2022
Neural Design for Genetic Perturbation Experiments
International Conference on Learning Representations (ICLR), 2022
Aldo Pacchiano
Drausin Wulsin
Robert A. Barton
L. Voloch
222
7
0
26 Jul 2022
Exploration in Linear Bandits with Rich Action Sets and its Implications for Inference
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Debangshu Banerjee
Avishek Ghosh
Sayak Ray Chowdhury
Aditya Gopalan
261
10
0
23 Jul 2022
Contextual Bandits with Smooth Regret: Efficient Learning in Continuous Action Spaces
International Conference on Machine Learning (ICML), 2022
Yinglun Zhu
Paul Mineiro
209
18
0
12 Jul 2022
Model Selection in Reinforcement Learning with General Function Approximations
Avishek Ghosh
Sayak Ray Chowdhury
121
3
0
06 Jul 2022
Best of Both Worlds Model Selection
Neural Information Processing Systems (NeurIPS), 2022
Aldo Pacchiano
Christoph Dann
Claudio Gentile
208
11
0
29 Jun 2022
Adversarial Bandits against Arbitrary Strategies
Jung-hun Kim
Se-Young Yun
388
0
0
30 May 2022
Breaking the
T
\sqrt{T}
T
Barrier: Instance-Independent Logarithmic Regret in Stochastic Contextual Linear Bandits
International Conference on Machine Learning (ICML), 2022
Avishek Ghosh
Abishek Sankararaman
171
5
0
19 May 2022
Nearly Optimal Algorithms for Linear Contextual Bandits with Adversarial Corruptions
Neural Information Processing Systems (NeurIPS), 2022
Jiafan He
Dongruo Zhou
Tong Zhang
Quanquan Gu
254
53
0
13 May 2022
Leveraging Initial Hints for Free in Stochastic Linear Bandits
International Conference on Algorithmic Learning Theory (ALT), 2022
Ashok Cutkosky
Christoph Dann
Abhimanyu Das
Qiuyi
Qiuyi Zhang
144
5
0
08 Mar 2022
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