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2003.01704
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Model Selection in Contextual Stochastic Bandit Problems
Neural Information Processing Systems (NeurIPS), 2020
3 March 2020
Aldo Pacchiano
My Phan
Yasin Abbasi-Yadkori
Anup B. Rao
Julian Zimmert
Tor Lattimore
Csaba Szepesvári
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Papers citing
"Model Selection in Contextual Stochastic Bandit Problems"
50 / 92 papers shown
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State-free Reinforcement Learning
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Stochastic Bandits Robust to Adversarial Attacks
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Causal Bandits: The Pareto Optimal Frontier of Adaptivity, a Reduction to Linear Bandits, and Limitations around Unknown Marginals
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Efficient Sequential Decision Making with Large Language Models
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Yinglun Zhu
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Bootstrapping Expectiles in Reinforcement Learning
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Online Bandits with (Biased) Offline Data: Adaptive Learning under Distribution Mismatch
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303
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Jonathan Lee
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Best-of-Both-Worlds Algorithms for Linear Contextual Bandits
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Alberto Rumi
Taira Tsuchiya
Fabio Vitale
Nicolò Cesa-Bianchi
338
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Online Clustering of Bandits with Misspecified User Models
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Zhiyong Wang
Jize Xie
Xutong Liu
Shuai Li
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394
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Anytime Model Selection in Linear Bandits
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N. Emmenegger
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Aldo Pacchiano
407
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Active Policy Improvement from Multiple Black-box Oracles
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Takuma Yoneda
Simon Mahns
Matthew R. Walter
Yuxin Chen
450
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Data-Driven Online Model Selection With Regret Guarantees
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Aldo Pacchiano
Christoph Dann
Claudio Gentile
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453
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05 Jun 2023
Robust Lipschitz Bandits to Adversarial Corruptions
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Cho-Jui Hsieh
T. C. Lee
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283
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Adaptation to Misspecified Kernel Regularity in Kernelised Bandits
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356
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26 Apr 2023
Best-of-Three-Worlds Linear Bandit Algorithm with Variance-Adaptive Regret Bounds
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Kei Takemura
192
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Estimating Optimal Policy Value in General Linear Contextual Bandits
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Weihao Kong
Aldo Pacchiano
Vidya Muthukumar
Emma Brunskill
283
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19 Feb 2023
Linear Bandits with Memory: from Rotting to Rising
Giulia Clerici
Pierre Laforgue
Nicolò Cesa-Bianchi
254
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Learning Complementary Policies for Human-AI Teams
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Maria De-Arteaga
364
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On the Complexity of Representation Learning in Contextual Linear Bandits
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Andrea Tirinzoni
Matteo Pirotta
A. Lazaric
258
1
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19 Dec 2022
Stochastic Rising Bandits
International Conference on Machine Learning (ICML), 2022
Alberto Maria Metelli
F. Trovò
Matteo Pirola
Marcello Restelli
200
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Contexts can be Cheap: Solving Stochastic Contextual Bandits with Linear Bandit Algorithms
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Osama A. Hanna
Lin F. Yang
Christina Fragouli
380
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Oracle Inequalities for Model Selection in Offline Reinforcement Learning
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George Tucker
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Emma Brunskill
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391
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Lifelong Bandit Optimization: No Prior and No Regret
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397
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Scalable Representation Learning in Linear Contextual Bandits with Constant Regret Guarantees
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Matteo Papini
Ahmed Touati
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306
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261
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Mononito Goswami
Cristian Challu
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499
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Drausin Wulsin
Robert A. Barton
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327
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Model Selection in Reinforcement Learning with General Function Approximations
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Sayak Ray Chowdhury
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Best of Both Worlds Model Selection
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250
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Adversarial Bandits against Arbitrary Strategies
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454
1
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Leveraging Initial Hints for Free in Stochastic Linear Bandits
International Conference on Algorithmic Learning Theory (ALT), 2022
Ashok Cutkosky
Christoph Dann
Abhimanyu Das
Qiuyi
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184
6
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Corralling a Larger Band of Bandits: A Case Study on Switching Regret for Linear Bandits
Annual Conference Computational Learning Theory (COLT), 2022
Haipeng Luo
Mengxiao Zhang
Peng Zhao
Zhi Zhou
261
22
0
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Model Selection in Batch Policy Optimization
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Jonathan Lee
George Tucker
Ofir Nachum
Bo Dai
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252
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Neural Pseudo-Label Optimism for the Bank Loan Problem
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Shaun Singh
Edward Chou
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Jakob N. Foerster
180
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Misspecified Gaussian Process Bandit Optimization
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266
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Universal and data-adaptive algorithms for model selection in linear contextual bandits
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Linear Contextual Bandits with Adversarial Corruptions
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471
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