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Heuristic-Guided Reinforcement Learning

Jun 05, 2021
Ching-An Cheng, Andrey Kolobov, Adith Swaminathan

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Improving Long-Term Metrics in Recommendation Systems using Short-Horizon Offline RL

Jun 01, 2021
Bogdan Mazoure, Paul Mineiro, Pavithra Srinath, Reza Sharifi Sedeh, Doina Precup, Adith Swaminathan

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Provably Good Batch Reinforcement Learning Without Great Exploration

Jul 22, 2020
Yao Liu, Adith Swaminathan, Alekh Agarwal, Emma Brunskill

* 36 pages, 7 figures 

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Improved Image Wasserstein Attacks and Defenses

Apr 26, 2020
J. Edward Hu, Adith Swaminathan, Hadi Salman, Greg Yang

* Best paper award at ICLR Trustworthy ML Workshop 2020 

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Working Memory Graphs

Nov 17, 2019
Ricky Loynd, Roland Fernandez, Asli Celikyilmaz, Adith Swaminathan, Matthew Hausknecht

* 9 pages, 6 figures, 6 page appendix 

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Learning Calibratable Policies using Programmatic Style-Consistency

Oct 02, 2019
Eric Zhan, Albert Tseng, Yisong Yue, Adith Swaminathan, Matthew Hausknecht

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Metareasoning in Modular Software Systems: On-the-Fly Configuration using Reinforcement Learning with Rich Contextual Representations

May 12, 2019
Aditya Modi, Debadeepta Dey, Alekh Agarwal, Adith Swaminathan, Besmira Nushi, Sean Andrist, Eric Horvitz

* 12 pages, 7 figures, 2 tables 

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Off-Policy Policy Gradient with State Distribution Correction

Apr 17, 2019
Yao Liu, Adith Swaminathan, Alekh Agarwal, Emma Brunskill

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Multi-Preference Actor Critic

Apr 05, 2019
Ishan Durugkar, Matthew Hausknecht, Adith Swaminathan, Patrick MacAlpine

* NeurIPS Workshop on Deep RL, 2018 

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NAIL: A General Interactive Fiction Agent

Feb 14, 2019
Matthew Hausknecht, Ricky Loynd, Greg Yang, Adith Swaminathan, Jason D. Williams

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Off-policy evaluation for slate recommendation

Nov 06, 2017
Adith Swaminathan, Akshay Krishnamurthy, Alekh Agarwal, Miroslav Dudík, John Langford, Damien Jose, Imed Zitouni

* 31 pages (9 main paper, 20 supplementary), 12 figures (2 main paper, 10 supplementary) 

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Large-scale Validation of Counterfactual Learning Methods: A Test-Bed

Jun 25, 2017
Damien Lefortier, Adith Swaminathan, Xiaotao Gu, Thorsten Joachims, Maarten de Rijke

* 10 pages, What If workshop NIPS 2016 

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Unbiased Learning-to-Rank with Biased Feedback

Aug 16, 2016
Thorsten Joachims, Adith Swaminathan, Tobias Schnabel

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Recommendations as Treatments: Debiasing Learning and Evaluation

May 27, 2016
Tobias Schnabel, Adith Swaminathan, Ashudeep Singh, Navin Chandak, Thorsten Joachims

* 10 pages in ICML 2016 

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Unbiased Comparative Evaluation of Ranking Functions

Apr 25, 2016
Tobias Schnabel, Adith Swaminathan, Peter Frazier, Thorsten Joachims

* Under review; 10 pages 

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Counterfactual Risk Minimization: Learning from Logged Bandit Feedback

May 20, 2015
Adith Swaminathan, Thorsten Joachims

* 10 pages 

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