Milind Tambe

ORCID

Publication Activity (10 Years)

Years Active: 1988-2024
Publications (10 Years): 257

Top Venues

Publications

Nikhil Behari, Edwin Zhang, Yunfan Zhao, Aparna Taneja, Dheeraj Nagaraj, Milind Tambe
A Decision-Language Model (DLM) for Dynamic Restless Multi-Armed Bandit Tasks in Public Health. CoRR (2024)
Biyonka Liang, Lily Xu, Aparna Taneja, Milind Tambe, Lucas Janson
A Bayesian Approach to Online Learning for Contextual Restless Bandits with Applications to Public Health. CoRR (2024)
Gargi Singh, Milind Tambe, Aparna Taneja
Towards Fairness constrained Restless Multi-Armed Bandits: a Case Study of Maternal and child Care Domain. Tiny Papers @ ICLR (2024)
Sanket Shah, Arun Sai Suggala, Milind Tambe, Aparna Taneja
Efficient Public Health Intervention Planning Using Decomposition-Based Decision-Focused Learning. CoRR (2024)
Niclas Boehmer, Minbiao Han, Haifeng Xu, Milind Tambe
Escape Sensing Games: Detection-vs-Evasion in Security Applications. CoRR (2024)
Lauren H. Cooke, Harvey Klyne, Edwin Zhang, Cassidy Laidlaw, Milind Tambe, Finale Doshi-Velez
Toward Computationally Efficient Inverse Reinforcement Learning via Reward Shaping. Tiny Papers @ ICLR (2024)
Niclas Boehmer, Yash Nair, Sanket Shah, Lucas Janson, Aparna Taneja, Milind Tambe
Evaluating the Effectiveness of Index-Based Treatment Allocation. CoRR (2024)
Sanket Shah, Arun Sai Suggala, Milind Tambe, Aparna Taneja
Efficient Public Health Intervention Planning Using Decomposition-Based Decision-focused Learning. AAMAS (2024)
Arshika Lalan, Shresth Verma, Paula Rodriguez Diaz, Panayiotis Danassis, Amrita Mahale, Kumar Madhu Sudan, Aparna Hegde, Milind Tambe, Aparna Taneja
Improving Health Information Access in the World's Largest Maternal Mobile Health Program via Bandit Algorithms. CoRR (2024)
Sanket Shah, Bryan Wilder, Andrew Perrault, Milind Tambe
Leaving the Nest: Going beyond Local Loss Functions for Predict-Then-Optimize. AAAI (2024)
Arpan Dasgupta, Niclas Boehmer, Neha Madhiwalla, Aparna Hedge, Bryan Wilder, Milind Tambe, Aparna Taneja
Preliminary Study of the Impact of AI-Based Interventions on Health and Behavioral Outcomes in Maternal Health Programs. CoRR (2024)
Edwin Zhang, Vincent Zhu, Naomi Saphra, Anat Kleiman, Benjamin L. Edelman, Milind Tambe, Sham M. Kakade, Eran Malach
Transcendence: Generative Models Can Outperform The Experts That Train Them. CoRR (2024)
David Rolnick, Alán Aspuru-Guzik, Sara Beery, Bistra Dilkina, Priya L. Donti, Marzyeh Ghassemi, Hannah Kerner, Claire Monteleoni, Esther Rolf, Milind Tambe, Adam White
Application-Driven Innovation in Machine Learning. CoRR (2024)
Soumyabrata Pal, Milind Tambe, Arun Sai Suggala, Karthikeyan Shanmugam, Aparna Taneja
Improving Mobile Maternal and Child Health Care Programs: Collaborative Bandits for Time Slot Selection. AAMAS (2024)
Arshika Lalan, Shresth Verma, Paula Rodriguez Diaz, Panayiotis Danassis, Amrita Mahale, Kumar Madhu Sudan, Aparna Hegde, Milind Tambe, Aparna Taneja
Improving Health Information Access in the World's Largest Maternal Mobile Health Program via Bandit Algorithms. AAAI (2024)
Edwin Zhang, Sadie Zhao, Tonghan Wang, Safwan Hossain, Henry Gasztowtt, Stephan Zheng, David C. Parkes, Milind Tambe, Yiling Chen
Social Environment Design. CoRR (2024)
Yunfan Zhao, Nikhil Behari, Edward Hughes, Edwin Zhang, Dheeraj Nagaraj, Karl Tuyls, Aparna Taneja, Milind Tambe
Towards Zero Shot Learning in Restless Multi-armed Bandits. AAMAS (2024)
Sonja Johnson-Yu, Kai Wang, Jessie Finocchiaro, Aparna Taneja, Milind Tambe
Modeling Robustness in Decision-Focused Learning as a Stackelberg Game. AAMAS (2023)
Kai Wang, Shresth Verma, Aditya Mate, Sanket Shah, Aparna Taneja, Neha Madhiwalla, Aparna Hegde, Milind Tambe
Scalable Decision-Focused Learning in Restless Multi-Armed Bandits with Application to Maternal and Child Health. AAAI (2023)
Shresth Verma, Gargi Singh, Aditya Mate, Paritosh Verma, Sruthi Gorantla, Neha Madhiwalla, Aparna Hegde, Divy Thakkar, Manish Jain, Milind Tambe, Aparna Taneja
Increasing Impact of Mobile Health Programs: SAHELI for Maternal and Child Care. AAAI (2023)
Paula Rodriguez Diaz, Jackson A. Killian, Lily Xu, Arun Sai Suggala, Aparna Taneja, Milind Tambe
Flexible Budgets in Restless Bandits: A Primal-Dual Algorithm for Efficient Budget Allocation. AAAI (2023)
Panayiotis Danassis, Shresth Verma, Jackson A. Killian, Aparna Taneja, Milind Tambe
Limited Resource Allocation in a Non-Markovian World: The Case of Maternal and Child Healthcare. CoRR (2023)
Abheek Ghosh, Dheeraj Nagaraj, Manish Jain, Milind Tambe
Indexability is Not Enough for Whittle: Improved, Near-Optimal Algorithms for Restless Bandits. AAMAS (2023)
Arpita Biswas, Jackson A. Killian, Paula Rodriguez Diaz, Susobhan Ghosh, Milind Tambe
Fairness for Workers Who Pull the Arms: An Index Based Policy for Allocation of Restless Bandit Tasks. AAMAS (2023)
Haipeng Chen, Bryan Wilder, Wei Qiu, Bo An, Eric Rice, Milind Tambe
Complex Contagion Influence Maximization: A Reinforcement Learning Approach. IJCAI (2023)
Aditya Mate, Bryan Wilder, Aparna Taneja, Milind Tambe
Improved Policy Evaluation for Randomized Trials of Algorithmic Resource Allocation. CoRR (2023)
Shresth Verma, Aditya Mate, Kai Wang, Neha Madhiwalla, Aparna Hegde, Aparna Taneja, Milind Tambe
Restless Multi-Armed Bandits for Maternal and Child Health: Results from Decision-Focused Learning. AAMAS (2023)
Aditya Mate, Bryan Wilder, Aparna Taneja, Milind Tambe
Improved Policy Evaluation for Randomized Trials of Algorithmic Resource Allocation. ICML (2023)
Panayiotis Danassis, Aris Filos-Ratsikas, Haipeng Chen, Milind Tambe, Boi Faltings
AI-driven Prices for Externalities and Sustainability in Production Markets. AAMAS (2023)
Paritosh Verma, Shresth Verma, Aditya Mate, Aparna Taneja, Milind Tambe
Decision-Focused Evaluation: Analyzing Performance of Deployed Restless Multi-Arm Bandits. CoRR (2023)
Arshika Lalan, Shresth Verma, Kumar Madhu Sudan, Amrita Mahale, Aparna Hegde, Milind Tambe, Aparna Taneja
Analyzing and Predicting Low-Listenership Trends in a Large-Scale Mobile Health Program: A Preliminary Investigation. CoRR (2023)
Sanket Shah, Andrew Perrault, Bryan Wilder, Milind Tambe
Leaving the Nest: Going Beyond Local Loss Functions for Predict-Then-Optimize. CoRR (2023)
Edward A. Cranford, Han-Ching Ou, Cleotilde Gonzalez, Milind Tambe, Christian Lebiere
Accounting for Uncertainty in Deceptive Signaling for Cybersecurity. HICSS (2023)
Kai Wang, Lily Xu, Aparna Taneja, Milind Tambe
Optimistic Whittle Index Policy: Online Learning for Restless Bandits. AAAI (2023)
Jackson A. Killian, Manish Jain, Yugang Jia, Jonathan Amar, Erich Huang, Milind Tambe
Equitable Restless Multi-Armed Bandits: A General Framework Inspired By Digital Health. CoRR (2023)
Arpita Biswas, Jackson A. Killian, Paula Rodriguez Diaz, Susobhan Ghosh, Milind Tambe
Fairness for Workers Who Pull the Arms: An Index Based Policy for Allocation of Restless Bandit Tasks. CoRR (2023)
Lauren H. Cooke, Harvey Klyne, Edwin Zhang, Cassidy Laidlaw, Milind Tambe, Finale Doshi-Velez
Toward Computationally Efficient Inverse Reinforcement Learning via Reward Shaping. CoRR (2023)
Lucia Gordon, Nikhil Behari, Samuel Collier, Elizabeth Bondi-Kelly, Jackson A. Killian, Catherine Ressijac, Peter Boucher, Andrew Davies, Milind Tambe
Find Rhinos without Finding Rhinos: Active Learning with Multimodal Imagery of South African Rhino Habitats. IJCAI (2023)
Elizabeth Bondi-Kelly, Haipeng Chen, Christopher D. Golden, Nikhil Behari, Milind Tambe
Predicting micronutrient deficiency with publicly available satellite data. AI Mag. 44 (1) (2023)
Yunfan Zhao, Nikhil Behari, Edward Hughes, Edwin Zhang, Dheeraj Nagaraj, Karl Tuyls, Aparna Taneja, Milind Tambe
Towards Zero Shot Learning in Restless Multi-armed Bandits. CoRR (2023)
Panayiotis Danassis, Shresth Verma, Jackson A. Killian, Aparna Taneja, Milind Tambe
Limited Resource Allocation in a Non-Markovian World: The Case of Maternal and Child Healthcare. IJCAI (2023)
Lily Xu, Esther Rolf, Sara Beery, Joseph R. Bennett, Tanya Y. Berger-Wolf, Tanya Birch, Elizabeth Bondi-Kelly, Justin Brashares, Melissa S. Chapman, Anthony Corso, Andrew Davies, Nikhil Garg, Angela Gaylard, Robert Heilmayr, Hannah Kerner, Konstantin Klemmer, Vipin Kumar, Lester Mackey, Claire Monteleoni, Paul Moorcroft, Jonathan Palmer, Andrew Perrault, David Thau, Milind Tambe
Reflections from the Workshop on AI-Assisted Decision Making for Conservation. CoRR (2023)
Jackson A. Killian, Arpita Biswas, Lily Xu, Shresth Verma, Vineet Nair, Aparna Taneja, Aparna Hegde, Neha Madhiwalla, Paula Rodriguez Diaz, Sonja Johnson-Yu, Milind Tambe
Robust Planning over Restless Groups: Engagement Interventions for a Large-Scale Maternal Telehealth Program. AAAI (2023)
Haipeng Chen, Bryan Wilder, Wei Qiu, Bo An, Eric Rice, Milind Tambe
A Learning Approach to Complex Contagion Influence Maximization. AAMAS (2023)
Shresth Verma, Gargi Singh, Aditya Mate, Paritosh Verma, Sruthi Gorantla, Neha Madhiwalla, Aparna Hegde, Divy Thakkar, Manish Jain, Milind Tambe, Aparna Taneja
Expanding impact of mobile health programs: SAHELI for maternal and child care. AI Mag. 44 (4) (2023)
Susobhan Ghosh, Pradeep Varakantham, Aniket Bhatkhande, Tamanna Ahmad, Anish Andheria, Wenjun Li, Aparna Taneja, Divy Thakkar, Milind Tambe
Facilitating Human-Wildlife Cohabitation through Conflict Prediction. AAAI (2022)
Palvi Aggarwal, Omkar Thakoor, Shahin Jabbari, Edward A. Cranford, Christian Lebiere, Milind Tambe, Cleotilde Gonzalez
Designing effective masking strategies for cyberdefense through human experimentation and cognitive models. Comput. Secur. 117 (2022)
Han-Ching Ou, Christoph Siebenbrunner, Jackson A. Killian, Meredith B. Brooks, David Kempe, Yevgeniy Vorobeychik, Milind Tambe
Networked Restless Multi-Armed Bandits for Mobile Interventions. AAMAS (2022)
Elizabeth Bondi, Haipeng Chen, Christopher D. Golden, Nikhil Behari, Milind Tambe
Micronutrient Deficiency Prediction via Publicly Available Satellite Data. AAAI (2022)
Siddhartha Banerjee, Sean R. Sinclair, Milind Tambe, Lily Xu, Christina Lee Yu
Artificial Replay: A Meta-Algorithm for Harnessing Historical Data in Bandits. CoRR (2022)
Zun Li, Feiran Jia, Aditya Mate, Shahin Jabbari, Mithun Chakraborty, Milind Tambe, Yevgeniy Vorobeychik
Solving structured hierarchical games using differential backward induction. UAI (2022)
Aditya S. Mate, Arpita Biswas, Christoph Siebenbrunner, Susobhan Ghosh, Milind Tambe
Efficient Algorithms for Finite Horizon and Streaming Restless Multi-Armed Bandit Problems. AAMAS (2022)
Kai Wang, Shresth Verma, Aditya Mate, Sanket Shah, Aparna Taneja, Neha Madhiwalla, Aparna Hegde, Milind Tambe
Decision-Focused Learning in Restless Multi-Armed Bandits with Application to Maternal and Child Care Domain. CoRR (2022)
Han-Ching Ou, Christoph Siebenbrunner, Jackson A. Killian, Meredith B. Brooks, David Kempe, Yevgeniy Vorobeychik, Milind Tambe
Networked Restless Multi-Armed Bandits for Mobile Interventions. CoRR (2022)
Aditya Mate, Lovish Madaan, Aparna Taneja, Neha Madhiwalla, Shresth Verma, Gargi Singh, Aparna Hegde, Pradeep Varakantham, Milind Tambe
Field Study in Deploying Restless Multi-Armed Bandits: Assisting Non-profits in Improving Maternal and Child Health. AAAI (2022)
Kai Wang, Lily Xu, Aparna Taneja, Milind Tambe
Optimistic Whittle Index Policy: Online Learning for Restless Bandits. CoRR (2022)
Peter Stone, Rodney Brooks, Erik Brynjolfsson, Ryan Calo, Oren Etzioni, Greg Hager, Julia Hirschberg, Shivaram Kalyanakrishnan, Ece Kamar, Sarit Kraus, Kevin Leyton-Brown, David C. Parkes, William H. Press, AnnaLee Saxenian, Julie Shah, Milind Tambe, Astro Teller
Artificial Intelligence and Life in 2030: The One Hundred Year Study on Artificial Intelligence. CoRR (2022)
Abheek Ghosh, Dheeraj Nagaraj, Manish Jain, Milind Tambe
Indexability is Not Enough for Whittle: Improved, Near-Optimal Algorithms for Restless Bandits. CoRR (2022)
Vineet Nair, Kritika Prakash, Michael Wilbur, Aparna Taneja, Corrine Namblard, Oyindamola Adeyemo, Abhishek Dubey, Abiodun Adereni, Milind Tambe, Ayan Mukhopadhyay
ADVISER: AI-Driven Vaccination Intervention Optimiser for Increasing Vaccine Uptake in Nigeria. CoRR (2022)
James Holt, Edward Raff, Ahmad Ridley, Dennis Ross, Arunesh Sinha, Diane Staheli, William Streilen, Milind Tambe, Yevgeniy Vorobeychik, Allan B. Wollaber
Artificial Intelligence for Cyber Security (AICS). CoRR (2022)
Milind Tambe
AI for Social Impact: Results from Deployments for Public Health and Conversation. KDD (2022)
Vineet Nair, Kritika Prakash, Michael Wilbur, Aparna Taneja, Corrine Namblard, Oyindamola Adeyemo, Abhishek Dubey, Abiodun Adereni, Milind Tambe, Ayan Mukhopadhyay
ADVISER: AI-Driven Vaccination Intervention Optimiser for Increasing Vaccine Uptake in Nigeria. IJCAI (2022)
Lily Xu, Arpita Biswas, Fei Fang, Milind Tambe
Ranked Prioritization of Groups in Combinatorial Bandit Allocation. CoRR (2022)
Jackson A. Killian, Lily Xu, Arpita Biswas, Milind Tambe
Restless and uncertain: Robust policies for restless bandits via deep multi-agent reinforcement learning. UAI (2022)
Sanket Shah, Kai Wang, Bryan Wilder, Andrew Perrault, Milind Tambe
Decision-Focused Learning without Decision-Making: Learning Locally Optimized Decision Losses. NeurIPS (2022)
Haipeng Chen, Susobhan Ghosh, Gregory Fan, Nikhil Behari, Arpita Biswas, Mollie Williams, Nancy E. Oriol, Milind Tambe
Using Public Data to Predict Demand for Mobile Health Clinics. AAAI (2022)
Kai Wang, Lily Xu, Andrew Perrault, Michael K. Reiter, Milind Tambe
Coordinating Followers to Reach Better Equilibria: End-to-End Gradient Descent for Stackelberg Games. AAAI (2022)
Lily Xu, Arpita Biswas, Fei Fang, Milind Tambe
Ranked Prioritization of Groups in Combinatorial Bandit Allocation. IJCAI (2022)
Adam Zychowski, Jacek Mandziuk, Elizabeth Bondi, Aravind Venugopal, Milind Tambe, Balaraman Ravindran
Evolutionary Approach to Security Games with Signaling. IJCAI (2022)
Adam Zychowski, Jacek Mandziuk, Elizabeth Bondi, Aravind Venugopal, Milind Tambe, Balaraman Ravindran
Evolutionary Approach to Security Games with Signaling. CoRR (2022)
Sanket Shah, Bryan Wilder, Andrew Perrault, Milind Tambe
Learning (Local) Surrogate Loss Functions for Predict-Then-Optimize Problems. CoRR (2022)
Lily Xu, Elizabeth Bondi, Fei Fang, Andrew Perrault, Kai Wang, Milind Tambe
Dual-Mandate Patrols: Multi-Armed Bandits for Green Security. AAAI (2021)
Edward A. Cranford, Cleotilde Gonzalez, Palvi Aggarwal, Milind Tambe, Sarah Cooney, Christian Lebiere
Towards a Cognitive Theory of Cyber Deception. Cogn. Sci. 45 (7) (2021)
Lily Xu, Andrew Perrault, Fei Fang, Haipeng Chen, Milind Tambe
Robust Reinforcement Learning Under Minimax Regret for Green Security. CoRR (2021)
Kai Wang, Lily Xu, Andrew Perrault, Michael K. Reiter, Milind Tambe
Coordinating Followers to Reach Better Equilibria: End-to-End Gradient Descent for Stackelberg Games. CoRR (2021)
Haipeng Chen, Wei Qiu, Han-Ching Ou, Bo An, Milind Tambe
Contingency-Aware Influence Maximization: A Reinforcement Learning Approach. CoRR (2021)
Kai Wang, Sanket Shah, Haipeng Chen, Andrew Perrault, Finale Doshi-Velez, Milind Tambe
Learning MDPs from Features: Predict-Then-Optimize for Sequential Decision Problems by Reinforcement Learning. CoRR (2021)
Aditya Mate, Andrew Perrault, Milind Tambe
Risk-Aware Interventions in Public Health: Planning with Restless Multi-Armed Bandits. AAMAS (2021)
Haipeng Chen, Wei Qiu, Han-Ching Ou, Bo An, Milind Tambe
Contingency-aware influence maximization: A reinforcement learning approach. UAI (2021)
Aida Rahmattalabi, Shahin Jabbari, Himabindu Lakkaraju, Phebe Vayanos, Max Izenberg, Ryan Brown, Eric Rice, Milind Tambe
Fair Influence Maximization: a Welfare Optimization Approach. AAAI (2021)
Han-Ching Ou, Haipeng Chen, Shahin Jabbari, Milind Tambe
Active Screening for Recurrent Diseases: A Reinforcement Learning Approach. AAMAS (2021)
Zun Li, Feiran Jia, Aditya Mate, Shahin Jabbari, Mithun Chakraborty, Milind Tambe, Yevgeniy Vorobeychik
Solving Structured Hierarchical Games Using Differential Backward Induction. CoRR (2021)
Kai Wang, Sanket Shah, Haipeng Chen, Andrew Perrault, Finale Doshi-Velez, Milind Tambe
Learning MDPs from Features: Predict-Then-Optimize for Sequential Decision Making by Reinforcement Learning. NeurIPS (2021)
Ramesha Karunasena, Mohammad Sarparajul Ambiya, Arunesh Sinha, Ruchit Nagar, Saachi Dalal, Hamid Abdullah, Divy Thakkar, Dhyanesh Narayanan, Milind Tambe
Measuring Data Collection Diligence for Community Healthcare. EAAMO (2021)
Siddharth Nishtala, Lovish Madaan, Aditya Mate, Harshavardhan Kamarthi, Anirudh Grama, Divy Thakkar, Dhyanesh Narayanan, Suresh Chaudhary, Neha Madhiwalla, Ramesh Padmanabhan, Aparna Hegde, Pradeep Varakantham, Balaraman Ravindran, Milind Tambe
Selective Intervention Planning using Restless Multi-Armed Bandits to Improve Maternal and Child Health Outcomes. CoRR (2021)
Bryan Wilder, Laura Onasch-Vera, Graham DiGuiseppi, Robin Petering, Chyna Hill, Amulya Yadav, Eric Rice, Milind Tambe
Clinical Trial of an AI-Augmented Intervention for HIV Prevention in Youth Experiencing Homelessness. AAAI (2021)
Lily Xu, Andrew Perrault, Fei Fang, Haipeng Chen, Milind Tambe
Robust reinforcement learning under minimax regret for green security. UAI (2021)
Han-Ching Ou, Haipeng Chen, Shahin Jabbari, Milind Tambe
Active Screening for Recurrent Diseases: A Reinforcement Learning Approach. CoRR (2021)
Feiran Jia, Aditya Mate, Zun Li, Shahin Jabbari, Mithun Chakraborty, Milind Tambe, Michael P. Wellman, Yevgeniy Vorobeychik
A Game-Theoretic Approach for Hierarchical Policy-Making. CoRR (2021)
Jackson A. Killian, Andrew Perrault, Milind Tambe
Beyond "To Act or Not to Act": Fast Lagrangian Approaches to General Multi-Action Restless Bandits. AAMAS (2021)
Aditya Mate, Lovish Madaan, Aparna Taneja, Neha Madhiwalla, Shresth Verma, Gargi Singh, Aparna Hegde, Pradeep Varakantham, Milind Tambe
Field Study in Deploying Restless Multi-Armed Bandits: Assisting Non-Profits in Improving Maternal and Child Health. CoRR (2021)
Aravind Venugopal, Elizabeth Bondi, Harshavardhan Kamarthi, Keval Dholakia, Balaraman Ravindran, Milind Tambe
Reinforcement Learning for Unified Allocation and Patrolling in Signaling Games with Uncertainty. AAMAS (2021)
Jackson A. Killian, Arpita Biswas, Sanket Shah, Milind Tambe
Q-Learning Lagrange Policies for Multi-Action Restless Bandits. CoRR (2021)
Alok Talekar, Sharad Shriram, Nidhin K. Vaidhiyan, Gaurav Aggarwal, Jiangzhuo Chen, Srinivasan Venkatramanan, Lijing Wang, Aniruddha Adiga, Adam Sadilek, Ashish Tendulkar, Madhav Marathe, Rajesh Sundaresan, Milind Tambe
Cohorting to Isolate Asymptomatic Spreaders: An Agent-Based Simulation Study on the Mumbai Suburban Railway. AAMAS (2021)
Arpita Biswas, Gaurav Aggarwal, Pradeep Varakantham, Milind Tambe
Learn to Intervene: An Adaptive Learning Policy for Restless Bandits in Application to Preventive Healthcare. CoRR (2021)
Jackson A. Killian, Lily Xu, Arpita Biswas, Milind Tambe
Robust Restless Bandits: Tackling Interval Uncertainty with Deep Reinforcement Learning. CoRR (2021)
Arpita Biswas, Gaurav Aggarwal, Pradeep Varakantham, Milind Tambe
Learning Index Policies for Restless Bandits with Application to Maternal Healthcare. AAMAS (2021)
Bryan Wilder, Michael J. Mina, Milind Tambe
Tracking Disease Outbreaks from Sparse Data with Bayesian Inference. AAAI (2021)
Arpita Biswas, Gaurav Aggarwal, Pradeep Varakantham, Milind Tambe
Learn to Intervene: An Adaptive Learning Policy for Restless Bandits in Application to Preventive Healthcare. IJCAI (2021)
Kai Wang, Bryan Wilder, Sze-Chuan Suen, Bistra Dilkina, Milind Tambe
Harnessing Heterogeneity: Learning from Decomposed Feedback in Bayesian Modeling. CoRR (2021)

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Publication Activity (10 Years)

Top Topics

Top Venues

Milind Tambe