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We propose Streaming Bandits, a Restless Multi Armed Bandit (RMAB) framework in which heterogeneous arms may arrive and leave the system after staying on for a finite lifetime.
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Learning to Prescribe Interventions for Tuberculosis Patients using Digital Adherence Data. In KDD
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The effects on tuberculosis treatment adherence from utilising community health workers: a comparison of selected rural and urban settings in Kenya
Jane Rahedi Ong’ang’o, Christina Mwachari, Hillary Kipruto, and Simon Karanja. 2014 · 2014
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A truthful budget feasible multi-armed bandit mechanism for crowdsourcing time critical tasks. In Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems . 1101–1109
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Restless poachers: Handling exploration-exploitation tradeoffs in security domains. In AAMAS
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An asymptotically optimal index policy for finite-horizon restless bandits
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Restless bandits visiting villages: A preliminary study on distributing public health services. In Proceedings of the 1st ACM SIGCAS Conference on Computing and Sustainable Societies . 1–8
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Age of information: Whittle index for scheduling stochastic arrivals. In 2018 IEEE International Symposium on Information Theory . IEEE
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Risk-Aware Interventions in Public Health: Planning with Restless Multi-Armed Bandits. In International Conference on Autonomous Agents and Multiagent Systems
Aditya Mate, Andrew Perrault, and Milind Tambe. 2021b
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Optimal screening for hepatocellular carcinoma: A restless bandit model
Elliot Lee, Mariel S Lavieri, and Michael Volk. 2019 · 2019
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An asymptotically optimal heuristic for general nonstationary finite-horizon restless multi-armed, multi-action bandits
Gabriel Zayas-Caban, Stefanus Jasin, and Guihua Wang. 2019 · 2019
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Faster dynamic matrix inverse for faster lps
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Collapsing Bandits and Their Application to Public Health Interventions. In Advances in Neural and Information Processing Systems (NeurIPS)
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Whittle index for AoI-aware scheduling. In IEEE International Conference on Communication Systems & Networks (COMSNETS) . IEEE
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Learn to Intervene: An Adaptive Learning Policy for Restless Bandits in Application to Preventive Healthcare. In Proceedings of the 30th International Joint Conference on Artificial Intelligence
Arpita Biswas, Gaurav Aggarwal, Pradeep Varakantham, and Milind Tambe. 2021 · 2021
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Aditya Mate, Lovish Madaan, Aparna Taneja, Neha Madhiwalla, Shresth Verma, Gargi Singh, Aparna Hegde, Pradeep Varakantham, and Milind Tambe. 2021a · 2021
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