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2012.13045
Cited By
Regret Bound Balancing and Elimination for Model Selection in Bandits and RL
24 December 2020
Aldo Pacchiano
Christoph Dann
Claudio Gentile
Peter L. Bartlett
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Papers citing
"Regret Bound Balancing and Elimination for Model Selection in Bandits and RL"
42 / 42 papers shown
Improved Training Mechanism for Reinforcement Learning via Online Model Selection
Aida Afshar
Aldo Pacchiano
84
0
0
01 Dec 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
390
51
0
31 Dec 2024
Model Selection for Average Reward RL with Application to Utility Maximization in Repeated Games
Alireza Masoumian
James R. Wright
564
2
0
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
501
4
0
14 Oct 2024
Learning Rate-Free Reinforcement Learning: A Case for Model Selection with Non-Stationary Objectives
Aida Afshar
Aldo Pacchiano
234
0
0
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
252
2
0
01 Jul 2024
Sparsity-Agnostic Linear Bandits with Adaptive Adversaries
Tianyuan Jin
Kyoungseok Jang
Nicolò Cesa-Bianchi
271
1
0
03 Jun 2024
Symmetric Linear Bandits with Hidden Symmetry
Nam-Phuong Tran
T. Ta
Debmalya Mandal
Long Tran-Thanh
417
1
0
22 May 2024
Experiment Planning with Function Approximation
Neural Information Processing Systems (NeurIPS), 2024
Aldo Pacchiano
Jonathan Lee
Emma Brunskill
OffRL
237
6
0
10 Jan 2024
Multitask Learning with No Regret: from Improved Confidence Bounds to Active Learning
Neural Information Processing Systems (NeurIPS), 2023
Pier Giuseppe Sessa
Pierre Laforgue
Nicolò Cesa-Bianchi
Andreas Krause
245
4
0
03 Aug 2023
Geometry-Aware Approaches for Balancing Performance and Theoretical Guarantees in Linear Bandits
International Conference on Learning Representations (ICLR), 2023
Yuwei Luo
Mohsen Bayati
406
2
0
26 Jun 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
453
11
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
356
3
0
26 Apr 2023
Data-Efficient Policy Selection for Navigation in Partial Maps via Subgoal-Based Abstraction
IEEE/RJS International Conference on Intelligent RObots and Systems (IROS), 2023
Abhishek Paudel
Gregory J. Stein
238
5
0
03 Apr 2023
Estimating Optimal Policy Value in General Linear Contextual Bandits
Jonathan Lee
Weihao Kong
Aldo Pacchiano
Vidya Muthukumar
Emma Brunskill
274
0
0
19 Feb 2023
Online Continuous Hyperparameter Optimization for Generalized Linear Contextual Bandits
Yue Kang
Cho-Jui Hsieh
T. C. Lee
372
2
0
18 Feb 2023
Stochastic Rising Bandits
International Conference on Machine Learning (ICML), 2022
Alberto Maria Metelli
F. Trovò
Matteo Pirola
Marcello Restelli
199
19
0
07 Dec 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
260
100
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
318
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
337
11
0
23 Jul 2022
Model Selection in Reinforcement Learning with General Function Approximations
Avishek Ghosh
Sayak Ray Chowdhury
190
3
0
06 Jul 2022
Best of Both Worlds Model Selection
Neural Information Processing Systems (NeurIPS), 2022
Aldo Pacchiano
Christoph Dann
Claudio Gentile
245
11
0
29 Jun 2022
Joint Representation Training in Sequential Tasks with Shared Structure
Aldo Pacchiano
Ofir Nachum
Nilseh Tripuraneni
Peter L. Bartlett
294
5
0
24 Jun 2022
Provable Benefits of Representational Transfer in Reinforcement Learning
Annual Conference Computational Learning Theory (COLT), 2022
Alekh Agarwal
Yuda Song
Wen Sun
Kaiwen Wang
Mengdi Wang
Xuezhou Zhang
OffRL
358
40
0
29 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
229
5
0
19 May 2022
Neural Pseudo-Label Optimism for the Bank Loan Problem
Neural Information Processing Systems (NeurIPS), 2021
Aldo Pacchiano
Shaun Singh
Edward Chou
Alexander C. Berg
Jakob N. Foerster
174
8
0
03 Dec 2021
Misspecified Gaussian Process Bandit Optimization
Neural Information Processing Systems (NeurIPS), 2021
Ilija Bogunovic
Andreas Krause
266
58
0
09 Nov 2021
Universal and data-adaptive algorithms for model selection in linear contextual bandits
Vidya Muthukumar
A. Krishnamurthy
307
5
0
08 Nov 2021
The Pareto Frontier of model selection for general Contextual Bandits
T. V. Marinov
Julian Zimmert
254
28
0
25 Oct 2021
Improved Algorithms for Misspecified Linear Markov Decision Processes
Daniel Vial
Advait Parulekar
Sanjay Shakkottai
R. Srikant
268
7
0
12 Sep 2021
Model Selection for Generic Reinforcement Learning
Avishek Ghosh
Sayak Ray Chowdhury
Kannan Ramchandran
267
1
0
13 Jul 2021
Model Selection for Generic Contextual Bandits
IEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2021
Avishek Ghosh
Abishek Sankararaman
Kannan Ramchandran
307
7
0
07 Jul 2021
Provably Efficient Representation Selection in Low-rank Markov Decision Processes: From Online to Offline RL
Conference on Uncertainty in Artificial Intelligence (UAI), 2021
Weitong Zhang
Jiafan He
Dongruo Zhou
Amy Zhang
Quanquan Gu
OffRL
307
12
0
22 Jun 2021
Towards Costless Model Selection in Contextual Bandits: A Bias-Variance Perspective
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
Sanath Kumar Krishnamurthy
Adrienne Margaret Propp
Susan Athey
334
5
0
11 Jun 2021
Feature and Parameter Selection in Stochastic Linear Bandits
International Conference on Machine Learning (ICML), 2021
Ahmadreza Moradipari
Berkay Turan
Yasin Abbasi-Yadkori
M. Alizadeh
Mohammad Ghavamzadeh
426
6
0
09 Jun 2021
Neural Active Learning with Performance Guarantees
Neural Information Processing Systems (NeurIPS), 2021
Pranjal Awasthi
Christoph Dann
Claudio Gentile
Ayush Sekhari
Zhilei Wang
195
25
0
06 Jun 2021
Leveraging Good Representations in Linear Contextual Bandits
International Conference on Machine Learning (ICML), 2021
Matteo Papini
Andrea Tirinzoni
Marcello Restelli
A. Lazaric
Matteo Pirotta
207
33
0
08 Apr 2021
Model-free Representation Learning and Exploration in Low-rank MDPs
Journal of machine learning research (JMLR), 2021
Aditya Modi
Jinglin Chen
A. Krishnamurthy
Nan Jiang
Alekh Agarwal
OffRL
376
87
0
14 Feb 2021
Pareto Optimal Model Selection in Linear Bandits
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
Yinglun Zhu
Robert D. Nowak
273
15
0
12 Feb 2021
Non-stationary Reinforcement Learning without Prior Knowledge: An Optimal Black-box Approach
Annual Conference Computational Learning Theory (COLT), 2021
Chen-Yu Wei
Haipeng Luo
OffRL
512
129
0
10 Feb 2021
Tactical Optimism and Pessimism for Deep Reinforcement Learning
Neural Information Processing Systems (NeurIPS), 2021
Theodore H. Moskovitz
Jack Parker-Holder
Aldo Pacchiano
Michael Arbel
Sai Li
492
71
0
07 Feb 2021
Model Selection in Contextual Stochastic Bandit Problems
Neural Information Processing Systems (NeurIPS), 2020
Aldo Pacchiano
My Phan
Yasin Abbasi-Yadkori
Anup B. Rao
Julian Zimmert
Tor Lattimore
Csaba Szepesvári
588
103
0
03 Mar 2020
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