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ORCIDMilind Tambe
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- affiliation: Harvard University, Cambridge, MA, USA
- affiliation (former): University of Southern California
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2020 – today
- 2023
[i72]Paritosh Verma, Shresth Verma, Aditya Mate, Aparna Taneja, Milind Tambe:
Decision-Focused Evaluation: Analyzing Performance of Deployed Restless Multi-Arm Bandits. CoRR abs/2301.07835 (2023)- 2022
- [j83]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: 102671 (2022) - [c392]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: 5219-5227 - [c391]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: 12017-12025 - [c390]Elizabeth Bondi, Haipeng Chen, Christopher D. Golden, Nikhil Behari, Milind Tambe:
Micronutrient Deficiency Prediction via Publicly Available Satellite Data. AAAI 2022: 12454-12460 - [c389]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: 12461-12467 - [c388]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: 12496-12502 - [c387]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: 880-888 - [c386]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: 1001-1009 - [c385]Adam Zychowski, Jacek Mandziuk, Elizabeth Bondi, Aravind Venugopal, Milind Tambe, Balaraman Ravindran:
Evolutionary Approach to Security Games with Signaling. IJCAI 2022: 620-627 - [c384]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: 5129-5135 - [c383]Lily Xu, Arpita Biswas, Fei Fang, Milind Tambe:
Ranked Prioritization of Groups in Combinatorial Bandit Allocation. IJCAI 2022: 5206-5212 - [c382]Milind Tambe:
AI for Social Impact: Results from Deployments for Public Health and Conversation. KDD 2022: 2 - [c381]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: 990-1000 - [c380]Zun Li, Feiran Jia, Aditya Mate, Shahin Jabbari, Mithun Chakraborty, Milind Tambe, Yevgeniy Vorobeychik:
Solving structured hierarchical games using differential backward induction. UAI 2022: 1107-1117 - [i71]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 abs/2201.12408 (2022) - [i70]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 abs/2202.00916 (2022) - [i69]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 abs/2202.14010 (2022) - [i68]Sanket Shah, Bryan Wilder, Andrew Perrault, Milind Tambe:
Learning (Local) Surrogate Loss Functions for Predict-Then-Optimize Problems. CoRR abs/2203.16067 (2022) - [i67]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 abs/2204.13663 (2022) - [i66]Adam Zychowski, Jacek Mandziuk, Elizabeth Bondi, Aravind Venugopal, Milind Tambe, Balaraman Ravindran:
Evolutionary Approach to Security Games with Signaling. CoRR abs/2204.14173 (2022) - [i65]Lily Xu, Arpita Biswas, Fei Fang, Milind Tambe:
Ranked Prioritization of Groups in Combinatorial Bandit Allocation. CoRR abs/2205.05659 (2022) - [i64]Kai Wang, Lily Xu, Aparna Taneja, Milind Tambe:
Optimistic Whittle Index Policy: Online Learning for Restless Bandits. CoRR abs/2205.15372 (2022) - [i63]Siddhartha Banerjee, Sean R. Sinclair, Milind Tambe, Lily Xu, Christina Lee Yu:
Artificial Replay: A Meta-Algorithm for Harnessing Historical Data in Bandits. CoRR abs/2210.00025 (2022) - [i62]Abheek Ghosh, Dheeraj Nagaraj, Manish Jain, Milind Tambe:
Indexability is Not Enough for Whittle: Improved, Near-Optimal Algorithms for Restless Bandits. CoRR abs/2211.00112 (2022) - [i61]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 abs/2211.06318 (2022) - 2021
- [j82]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) - [j81]Bryan Wilder, Sze-Chuan Suen, Milind Tambe:
Allocating outreach resources for disease control in a dynamic population with information spread. IISE Trans. 53(6): 629-642 (2021) - [c379]Bryan Wilder, Michael J. Mina, Milind Tambe:
Tracking Disease Outbreaks from Sparse Data with Bayesian Inference. AAAI 2021: 4883-4891 - [c378]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: 11630-11638 - [c377]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: 14948-14956 - [c376]Lily Xu, Elizabeth Bondi, Fei Fang, Andrew Perrault, Kai Wang, Milind Tambe:
Dual-Mandate Patrols: Multi-Armed Bandits for Green Security. AAAI 2021: 14974-14982 - [c375]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: 710-718 - [c374]Aditya Mate, Andrew Perrault, Milind Tambe:
Risk-Aware Interventions in Public Health: Planning with Restless Multi-Armed Bandits. AAMAS 2021: 880-888 - [c373]Han-Ching Ou, Haipeng Chen, Shahin Jabbari, Milind Tambe:
Active Screening for Recurrent Diseases: A Reinforcement Learning Approach. AAMAS 2021: 992-1000 - [c372]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: 1353-1361 - [c371]Arpita Biswas, Gaurav Aggarwal, Pradeep Varakantham, Milind Tambe:
Learning Index Policies for Restless Bandits with Application to Maternal Healthcare. AAMAS 2021: 1467-1468 - [c370]Alok Talekar, Sharad Shriram, Nidhin K. Vaidhiyan, Gaurav Aggarwal, Jiangzhuo Chen, Srinivasan Venkatramanan, Lijing Wang, Aniruddha Adiga, Adam Sadilek, Ashish Tendulkar, Madhav V. Marathe, Rajesh Sundaresan, Milind Tambe:
Cohorting to Isolate Asymptomatic Spreaders: An Agent-Based Simulation Study on the Mumbai Suburban Railway. AAMAS 2021: 1680-1682 - [c369]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: 10:1-10:12 - [c368]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: 4039-4046 - [c367]Jackson A. Killian, Arpita Biswas, Sanket Shah, Milind Tambe:
Q-Learning Lagrange Policies for Multi-Action Restless Bandits. KDD 2021: 871-881 - [c366]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: 8795-8806 - [c365]Lily Xu, Andrew Perrault, Fei Fang, Haipeng Chen, Milind Tambe:
Robust reinforcement learning under minimax regret for green security. UAI 2021: 257-267 - [c364]Haipeng Chen, Wei Qiu, Han-Ching Ou, Bo An, Milind Tambe:
Contingency-aware influence maximization: A reinforcement learning approach. UAI 2021: 1535-1545 - [i60]Han-Ching Ou, Haipeng Chen, Shahin Jabbari, Milind Tambe:
Active Screening for Recurrent Diseases: A Reinforcement Learning Approach. CoRR abs/2101.02766 (2021) - [i59]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 abs/2102.10646 (2021) - [i58]Aditya Mate, Arpita Biswas, Christoph Siebenbrunner, Milind Tambe:
Efficient Algorithms for Finite Horizon and Streaming Restless Multi-Armed Bandit Problems. CoRR abs/2103.04730 (2021) - [i57]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 abs/2103.09052 (2021) - [i56]Arpita Biswas, Gaurav Aggarwal, Pradeep Varakantham, Milind Tambe:
Learn to Intervene: An Adaptive Learning Policy for Restless Bandits in Application to Preventive Healthcare. CoRR abs/2105.07965 (2021) - [i55]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 abs/2106.03278 (2021) - [i54]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 abs/2106.03279 (2021) - [i53]Zun Li, Feiran Jia, Aditya Mate, Shahin Jabbari, Mithun Chakraborty, Milind Tambe, Yevgeniy Vorobeychik:
Solving Structured Hierarchical Games Using Differential Backward Induction. CoRR abs/2106.04663 (2021) - [i52]Haipeng Chen, Wei Qiu, Han-Ching Ou, Bo An, Milind Tambe:
Contingency-Aware Influence Maximization: A Reinforcement Learning Approach. CoRR abs/2106.07039 (2021) - [i51]Lily Xu, Andrew Perrault, Fei Fang, Haipeng Chen, Milind Tambe:
Robust Reinforcement Learning Under Minimax Regret for Green Security. CoRR abs/2106.08413 (2021) - [i50]Jackson A. Killian, Arpita Biswas, Sanket Shah, Milind Tambe:
Q-Learning Lagrange Policies for Multi-Action Restless Bandits. CoRR abs/2106.12024 (2021) - [i49]Jackson A. Killian, Lily Xu, Arpita Biswas, Milind Tambe:
Robust Restless Bandits: Tackling Interval Uncertainty with Deep Reinforcement Learning. CoRR abs/2107.01689 (2021) - [i48]Kai Wang, Bryan Wilder, Sze-Chuan Suen, Bistra Dilkina, Milind Tambe:
Harnessing Heterogeneity: Learning from Decomposed Feedback in Bayesian Modeling. CoRR abs/2107.03003 (2021) - [i47]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 abs/2109.08075 (2021) - [i46]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. CoRR abs/2109.10637 (2021) - 2020
- [j80]Andrew Perrault, Fei Fang, Arunesh Sinha, Milind Tambe:
Artificial Intelligence for Social Impact: Learning and Planning in the Data-to-Deployment Pipeline. AI Mag. 41(4): 3-16 (2020) - [j79]Lindsay E. Young, Jerome R. Mayaud, Sze-Chuan Suen, Milind Tambe, Eric Rice:
Modeling the dynamism of HIV information diffusion in multiplex networks of homeless youth. Soc. Networks 63: 112-121 (2020) - [j78]Edward A. Cranford, Cleotilde Gonzalez, Palvi Aggarwal, Sarah Cooney, Milind Tambe, Christian Lebiere:
Toward Personalized Deceptive Signaling for Cyber Defense Using Cognitive Models. Top. Cogn. Sci. 12(3): 992-1011 (2020) - [c363]Elizabeth Bondi, Hoon Oh, Haifeng Xu, Fei Fang, Bistra Dilkina, Milind Tambe:
To Signal or Not To Signal: Exploiting Uncertain Real-Time Information in Signaling Games for Security and Sustainability. AAAI 2020: 1369-1377 - [c362]Andrew Perrault, Bryan Wilder, Eric Ewing, Aditya Mate, Bistra Dilkina, Milind Tambe:
End-to-End Game-Focused Learning of Adversary Behavior in Security Games. AAAI 2020: 1378-1386 - [c361]Aaron M. Ferber, Bryan Wilder, Bistra Dilkina, Milind Tambe:
MIPaaL: Mixed Integer Program as a Layer. AAAI 2020: 1504-1511 - [c360]Sanket Shah, Arunesh Sinha, Pradeep Varakantham, Andrew Perrault, Milind Tambe:
Solving Online Threat Screening Games using Constrained Action Space Reinforcement Learning. AAAI 2020: 2226-2235 - [c359]Harshavardhan Kamarthi, Priyesh Vijayan, Bryan Wilder, Balaraman Ravindran, Milind Tambe:
Influence Maximization in Unknown Social Networks: Learning Policies for Effective Graph Sampling. AAMAS 2020: 575-583 - [c358]Han-Ching Ou, Arunesh Sinha, Sze-Chuan Suen, Andrew Perrault, Alpan Raval, Milind Tambe:
Who and When to Screen: Multi-Round Active Screening for Network Recurrent Infectious Diseases Under Uncertainty. AAMAS 2020: 992-1000 - [c357]Kai Wang, Andrew Perrault, Aditya Mate, Milind Tambe:
Scalable Game-Focused Learning of Adversary Models: Data-to-Decisions in Network Security Games. AAMAS 2020: 1449-1457 - [c356]Omkar Thakoor, Shahin Jabbari, Palvi Aggarwal, Cleotilde Gonzalez, Milind Tambe, Phebe Vayanos:
Exploiting Bounded Rationality in Risk-Based Cyber Camouflage Games. GameSec 2020: 103-124 - [c355]Edward A. Cranford, Cleotilde Gonzalez, Palvi Aggarwal, Sarah Cooney, Milind Tambe, Christian Lebiere:
Adaptive Cyber Deception: Cognitively Informed Signaling for Cyber Defense. HICSS 2020: 1-10 - [c354]Lily Xu, Shahrzad Gholami, Sara Mc Carthy, Bistra Dilkina, Andrew J. Plumptre, Milind Tambe, Rohit Singh, Mustapha Nsabuga, Joshua Mabonga, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba, Tom Okello, Eric Enyel:
Stay Ahead of Poachers: Illegal Wildlife Poaching Prediction and Patrol Planning Under Uncertainty with Field Test Evaluations (Short Version). ICDE 2020: 1898-1901 - [c353]Han-Ching Ou, Kai Wang, Finale Doshi-Velez, Milind Tambe:
Active Screening on Recurrent Diseases Contact Networks with Uncertainty: A Reinforcement Learning Approach. MABS 2020: 54-65 - [c352]Kai Wang, Bryan Wilder, Andrew Perrault, Milind Tambe:
Automatically Learning Compact Quality-aware Surrogates for Optimization Problems. NeurIPS 2020 - [c351]Aditya Mate, Jackson A. Killian, Haifeng Xu, Andrew Perrault, Milind Tambe:
Collapsing Bandits and Their Application to Public Health Intervention. NeurIPS 2020 - [c350]Ayan Mukhopadhyay, Kai Wang, Andrew Perrault, Mykel J. Kochenderfer, Milind Tambe, Yevgeniy Vorobeychik:
Robust Spatial-Temporal Incident Prediction. UAI 2020: 360-369 - [c349]Elizabeth Bondi, Raghav Jain, Palash Aggrawal, Saket Anand, Robert Hannaford, Ashish Kapoor, Jim Piavis, Shital Shah, Lucas Joppa, Bistra Dilkina, Milind Tambe:
BIRDSAI: A Dataset for Detection and Tracking in Aerial Thermal Infrared Videos. WACV 2020: 1736-1745 - [p8]Aaron Schlenker, Omkar Thakoor, Haifeng Xu, Fei Fang, Milind Tambe, Phebe Vayanos:
Game Theoretic Cyber Deception to Foil Adversarial Network Reconnaissance. Adaptive Autonomous Secure Cyber Systems 2020: 183-204 - [i45]Andrew Perrault, Fei Fang, Arunesh Sinha, Milind Tambe:
AI for Social Impact: Learning and Planning in the Data-to-Deployment Pipeline. CoRR abs/2001.00088 (2020) - [i44]Aida Rahmattalabi, Phebe Vayanos, Anthony Fulginiti, Eric Rice, Bryan Wilder, Amulya Yadav, Milind Tambe:
Exploring Algorithmic Fairness in Robust Graph Covering Problems. CoRR abs/2006.06865 (2020) - [i43]Siddharth Nishtala, Harshavardhan Kamarthi, Divy Thakkar, Dhyanesh Narayanan, Anirudh Grama, Ramesh Padmanabhan, Neha Madhiwalla, Suresh Chaudhary, Balaraman Ravindran, Milind Tambe:
Missed calls, Automated Calls and Health Support: Using AI to improve maternal health outcomes by increasing program engagement. CoRR abs/2006.07590 (2020) - [i42]Aida Rahmattalabi, Shahin Jabbari, Himabindu Lakkaraju, Phebe Vayanos, Eric Rice, Milind Tambe:
Fair Influence Maximization: A Welfare Optimization Approach. CoRR abs/2006.07906 (2020) - [i41]Kai Wang, Bryan Wilder, Andrew Perrault, Milind Tambe:
Automatically Learning Compact Quality-aware Surrogates for Optimization Problems. CoRR abs/2006.10815 (2020) - [i40]Lily Xu, Andrew Perrault, Andrew J. Plumptre, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba, Milind Tambe:
Game Theory on the Ground: The Effect of Increased Patrols on Deterring Poachers. CoRR abs/2006.12411 (2020) - [i39]Aditya Mate, Jackson A. Killian, Haifeng Xu, Andrew Perrault, Milind Tambe:
Collapsing Bandits and Their Application to Public Health Interventions. CoRR abs/2007.04432 (2020) - [i38]Eric Rice, Laura Onasch-Vera, Graham T. DiGuiseppi, Bryan Wilder, Robin Petering, Chyna Hill, Amulya Yadav, Milind Tambe:
Preliminary Results from a Peer-Led, Social Network Intervention, Augmented by Artificial Intelligence to Prevent HIV among Youth Experiencing Homelessness. CoRR abs/2007.07747 (2020) - [i37]Bryan Wilder, Michael J. Mina, Milind Tambe:
Tracking disease outbreaks from sparse data with Bayesian inference. CoRR abs/2009.05863 (2020) - [i36]Lily Xu, Elizabeth Bondi, Fei Fang, Andrew Perrault, Kai Wang, Milind Tambe:
Dual-Mandate Patrols: Multi-Armed Bandits for Green Security. CoRR abs/2009.06560 (2020) - [i35]Bryan Wilder, Laura Onasch-Vera, Graham T. 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. CoRR abs/2009.09559 (2020) - [i34]Ramesha Karunasena, Mohammad Sarparajul Ambiya, Arunesh Sinha, Ruchit Nagar, Saachi Dalal, Divy Thakkar, Milind Tambe:
Measuring Data Collection Quality for Community Healthcare. CoRR abs/2011.02962 (2020) - [i33]Rachel Guo, Lily Xu, Drew Cronin, Francis Okeke, Andrew J. Plumptre, Milind Tambe:
Enhancing Poaching Predictions for Under-Resourced Wildlife Conservation Parks Using Remote Sensing Imagery. CoRR abs/2011.10666 (2020) - [i32]Xinrun Wang, Tarun Nair, Haoyang Li, Yuh Sheng Reuben Wong, Nachiket Kelkar, Srinivas Vaidyanathan, Rajat Nayak, Bo An, Jagdish Krishnaswamy, Milind Tambe:
Efficient Reservoir Management through Deep Reinforcement Learning. CoRR abs/2012.03822 (2020) - [i31]Aravind Venugopal, Elizabeth Bondi, Harshavardhan Kamarthi, Keval Dholakia, Balaraman Ravindran, Milind Tambe:
Reinforcement Learning for Unified Allocation and Patrolling in Signaling Games with Uncertainty. CoRR abs/2012.10389 (2020) - [i30]Alok Talekar, Sharad Shriram, Nidhin K. Vaidhiyan, Gaurav Aggarwal, Jiangzhuo Chen, Srinivasan Venkatramanan, Lijing Wang, Aniruddha Adiga, Adam Sadilek, Ashish Tendulkar, Madhav V. Marathe, Rajesh Sundaresan, Milind Tambe:
Cohorting to isolate asymptomatic spreaders: An agent-based simulation study on the Mumbai Suburban Railway. CoRR abs/2012.12839 (2020)
2010 – 2019
- 2019
- [j77]Carla P. Gomes, Thomas G. Dietterich, Christopher Barrett, Jon Conrad, Bistra Dilkina, Stefano Ermon, Fei Fang, Andrew Farnsworth, Alan Fern, Xiaoli Z. Fern, Daniel Fink, Douglas H. Fisher, Alexander Flecker, Daniel Freund, Angela Fuller, John M. Gregoire, John E. Hopcroft, Steve Kelling, J. Zico Kolter, Warren B. Powell, Nicole D. Sintov, John S. Selker, Bart Selman, Daniel Sheldon, David B. Shmoys, Milind Tambe, Weng-Keen Wong, Christopher Wood, Xiaojian Wu, Yexiang Xue, Amulya Yadav, Abdul-Aziz Yakubu, Mary Lou Zeeman:
Computational sustainability: computing for a better world and a sustainable future. Commun. ACM 62(9): 56-65 (2019) - [c348]Bryan Wilder, Bistra Dilkina, Milind Tambe:
Melding the Data-Decisions Pipeline: Decision-Focused Learning for Combinatorial Optimization. AAAI 2019: 1658-1665 - [c347]Qingyu Guo, Jiarui Gan, Fei Fang, Long Tran-Thanh, Milind Tambe, Bo An:
On the Inducibility of Stackelberg Equilibrium for Security Games. AAAI 2019: 2020-2028 - [c346]Shahrzad Gholami, Amulya Yadav, Long Tran-Thanh, Bistra Dilkina, Milind Tambe:
Don't Put All Your Strategies in One Basket: Playing Green Security Games with Imperfect Prior Knowledge. AAMAS 2019: 395-403 - [c345]Elizabeth Bondi, Hoon Oh, Haifeng Xu, Fei Fang, Bistra Dilkina, Milind Tambe:
Broken Signals in Security Games: Coordinating Patrollers and Sensors in the Real World. AAMAS 2019: 1838-1840 - [c344]Sarah Cooney, Phebe Vayanos, Thanh Hong Nguyen, Cleotilde Gonzalez, Christian Lebiere, Edward A. Cranford, Milind Tambe:
Warning Time: Optimizing Strategic Signaling for Security Against Boundedly Rational Adversaries. AAMAS 2019: 1892-1894 - [c343]Nitin Kamra, Umang Gupta, Kai Wang, Fei Fang, Yan Liu, Milind Tambe:
Deep Fictitious Play for Games with Continuous Action Spaces. AAMAS 2019: 2042-2044 - [c342]Aida Rahmattalabi, Phebe Vayanos, Anthony Fulginiti, Milind Tambe:
Robust Peer-Monitoring on Graphs with an Application to Suicide Prevention in Social Networks. AAMAS 2019: 2168-2170 - [c341]Omkar Thakoor, Milind Tambe, Phebe Vayanos, Haifeng Xu, Christopher Kiekintveld:
General-Sum Cyber Deception Games under Partial Attacker Valuation Information. AAMAS 2019: 2215-2217 - [c340]Elizabeth Bondi, Hoon Oh, Haifeng Xu, Fei Fang, Bistra Dilkina, Milind Tambe:
Using Game Theory in Real Time in the Real World: A Conservation Case Study. AAMAS 2019: 2336-2338 - [c339]Nitin Kamra, Umang Gupta, Kai Wang, Fei Fang, Yan Liu, Milind Tambe:
DeepFP for Finding Nash Equilibrium in Continuous Action Spaces. GameSec 2019: 238-258 - [c338]Omkar Thakoor, Milind Tambe, Phebe Vayanos, Haifeng Xu, Christopher Kiekintveld, Fei Fang:
Cyber Camouflage Games for Strategic Deception. GameSec 2019: 525-541 - [c337]Xinrun Wang, Milind Tambe, Branislav Bosanský, Bo An:
When Players Affect Target Values: Modeling and Solving Dynamic Partially Observable Security Games. GameSec 2019: 542-562 - [c336]Alan Tsang, Bryan Wilder, Eric Rice, Milind Tambe, Yair Zick:
Group-Fairness in Influence Maximization. IJCAI 2019: 5997-6005 - [c335]Jackson A. Killian, Bryan Wilder, Amit Sharma, Vinod Choudhary, Bistra Dilkina, Milind Tambe:
Learning to Prescribe Interventions for Tuberculosis Patients Using Digital Adherence Data. KDD 2019: 2430-2438 - [c334]Bryan Wilder, Eric Ewing, Bistra Dilkina, Milind Tambe:
End to end learning and optimization on graphs. NeurIPS 2019: 4674-4685 - [c333]Aida Rahmattalabi, Phebe Vayanos, Anthony Fulginiti, Eric Rice, Bryan Wilder, Amulya Yadav, Milind Tambe:
Exploring Algorithmic Fairness in Robust Graph Covering Problems. NeurIPS 2019: 15750-15761 - [c332]Kai Wang, Bryan Wilder, Sze-Chuan Suen, Bistra Dilkina, Milind Tambe:
Improving GP-UCB Algorithm by Harnessing Decomposed Feedback. PKDD/ECML Workshops (1) 2019: 555-569 - [c331]