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Ranked Prioritization of Groups in Combinatorial Bandit Allocation


May 11, 2022
Lily Xu, Arpita Biswas, Fei Fang, Milind Tambe

* Accepted at IJCAI 2022, AI for Good track. 7 pages + 2 pages appendix. Code is available at https://github.com/lily-x/rankedCUCB 

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Towards Fair Recommendation in Two-Sided Platforms


Dec 26, 2021
Arpita Biswas, Gourab K Patro, Niloy Ganguly, Krishna P. Gummadi, Abhijnan Chakraborty

* ACM Transactions on the Web, Volume 16, Issue 2 May 2022, Article no 8. arXiv admin note: substantial text overlap with arXiv:2002.10764 

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Robust Restless Bandits: Tackling Interval Uncertainty with Deep Reinforcement Learning


Jul 04, 2021
Jackson A. Killian, Lily Xu, Arpita Biswas, Milind Tambe

* 18 pages, 3 figures 

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Q-Learning Lagrange Policies for Multi-Action Restless Bandits


Jun 22, 2021
Jackson A. Killian, Arpita Biswas, Sanket Shah, Milind Tambe

* 13 pages, 6 figures, to be published in Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data 

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Learn to Intervene: An Adaptive Learning Policy for Restless Bandits in Application to Preventive Healthcare


May 17, 2021
Arpita Biswas, Gaurav Aggarwal, Pradeep Varakantham, Milind Tambe

* To appear in the 30th International Joint Conference on Artificial Intelligence (IJCAI 2021) 

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Efficient Algorithms for Finite Horizon and Streaming Restless Multi-Armed Bandit Problems


Mar 08, 2021
Aditya Mate, Arpita Biswas, Christoph Siebenbrunner, Milind Tambe


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Ensuring Fairness under Prior Probability Shifts


May 06, 2020
Arpita Biswas, Suvam Mukherjee


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COVID-19: Strategies for Allocation of Test Kits


Apr 03, 2020
Arpita Biswas, Shruthi Bannur, Prateek Jain, Srujana Merugu


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FairRec: Two-Sided Fairness for Personalized Recommendations in Two-Sided Platforms


Feb 25, 2020
Gourab K. Patro, Arpita Biswas, Niloy Ganguly, Krishna P. Gummadi, Abhijnan Chakraborty


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Quantifying Infra-Marginality and Its Trade-off with Group Fairness


Sep 03, 2019
Arpita Biswas, Siddharth Barman, Amit Deshpande, Amit Sharma


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