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A Contextual Bandit Approach for Learning to Plan in Environments with Probabilistic Goal Configurations


Nov 29, 2022
Sohan Rudra, Saksham Goel, Anirban Santara, Claudio Gentile, Laurent Perron, Fei Xia, Vikas Sindhwani, Carolina Parada, Gaurav Aggarwal

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* Shorter version accepted at NeurIPS 2022 Workshop on Robot Learning: Trustworthy Robotics 

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Best of Both Worlds Model Selection


Jun 29, 2022
Aldo Pacchiano, Christoph Dann, Claudio Gentile

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* 10 pages in main, 43 pages appendix 

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Achieving Minimax Rates in Pool-Based Batch Active Learning


Feb 11, 2022
Claudio Gentile, Zhilei Wang, Tong Zhang

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Nonstochastic Bandits with Composite Anonymous Feedback


Dec 06, 2021
Nicolò Cesa-Bianchi, Tommaso Cesari, Roberto Colomboni, Claudio Gentile, Yishay Mansour

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Batch Active Learning at Scale


Jul 29, 2021
Gui Citovsky, Giulia DeSalvo, Claudio Gentile, Lazaros Karydas, Anand Rajagopalan, Afshin Rostamizadeh, Sanjiv Kumar

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Adapting to Misspecification in Contextual Bandits


Jul 12, 2021
Dylan J. Foster, Claudio Gentile, Mehryar Mohri, Julian Zimmert

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* Appeared at NeurIPS 2020 

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On Learning to Rank Long Sequences with Contextual Bandits


Jun 07, 2021
Anirban Santara, Claudio Gentile, Gaurav Aggarwal, Shuai Li

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Neural Active Learning with Performance Guarantees


Jun 06, 2021
Pranjal Awasthi, Christoph Dann, Claudio Gentile, Ayush Sekhari, Zhilei Wang

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* 30 pages 

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Regret Bound Balancing and Elimination for Model Selection in Bandits and RL


Dec 24, 2020
Aldo Pacchiano, Christoph Dann, Claudio Gentile, Peter Bartlett

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* 57 pages 

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Online Model Selection: a Rested Bandit Formulation


Dec 07, 2020
Leonardo Cella, Claudio Gentile, Massimiliano Pontil

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