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Viewing Publication 1 - 100 from 513

2024

Toward Computationally Efficient Inverse Reinforcement Learning via Reward ShapingLauren H. Cooke, Harvey Klyne, Edwin Zhang, Cassidy Laidlaw, Milind Tambe, Finale Doshi-Velez. iclr 2024: [doi]

Improving Health Information Access in the World's Largest Maternal Mobile Health Program via Bandit AlgorithmsArshika Lalan, Shresth Verma, Paula Rodriguez Diaz, Panayiotis Danassis, Amrita Mahale, Kumar Madhu Sudan, Aparna Hegde, Milind Tambe, Aparna Taneja. AAAI 2024: 22913-22919 [doi]

Improving Mobile Maternal and Child Health Care Programs: Collaborative Bandits for Time Slot SelectionSoumyabrata Pal, Milind Tambe, Arun Sai Suggala, Karthikeyan Shanmugam, Aparna Taneja. atal 2024: 1540-1548 [doi]

Position: Application-Driven Innovation in Machine LearningDavid Rolnick, Alán Aspuru-Guzik, Sara Beery, Bistra Dilkina, Priya L. Donti, Marzyeh Ghassemi, Hannah Kerner, Claire Monteleoni, Esther Rolf, Milind Tambe, Adam White. icml 2024: [doi]

Efficient Public Health Intervention Planning Using Decomposition-Based Decision-focused LearningSanket Shah, Arun Sai Suggala, Milind Tambe, Aparna Taneja. atal 2024: 1701-1709 [doi]

Leaving the Nest: Going beyond Local Loss Functions for Predict-Then-OptimizeSanket Shah, Bryan Wilder, Andrew Perrault, Milind Tambe. AAAI 2024: 14902-14909 [doi]

Towards Fairness constrained Restless Multi-Armed Bandits: a Case Study of Maternal and child Care DomainGargi Singh, Milind Tambe, Aparna Taneja. iclr 2024: [doi]

Position: Social Environment Design Should be Further Developed for AI-based Policy-MakingEdwin Zhang, Sadie Zhao, Tonghan Wang 0003, Safwan Hossain, Henry Gasztowtt, Stephan Zheng, David C. Parkes, Milind Tambe, Yiling Chen 0001. icml 2024: [doi]

Towards Zero Shot Learning in Restless Multi-armed BanditsYunfan Zhao, Nikhil Behari, Edward Hughes 0001, Edwin Zhang, Dheeraj Nagaraj, Karl Tuyls, Aparna Taneja, Milind Tambe. atal 2024: 2618-2620 [doi]

2023

A Learning Approach to Complex Contagion Influence MaximizationHaipeng Chen 0001, Bryan Wilder, Wei Qiu 0001, Bo An 0001, Eric Rice, Milind Tambe. atal 2023: 2622-2624 [doi]

Complex Contagion Influence Maximization: A Reinforcement Learning ApproachHaipeng Chen 0001, Bryan Wilder, Wei Qiu 0001, Bo An 0001, Eric Rice, Milind Tambe. IJCAI 2023: 5531-5540 [doi]

Optimistic Whittle Index Policy: Online Learning for Restless BanditsKai Wang 0040, Lily Xu, Aparna Taneja, Milind Tambe. AAAI 2023: 10131-10139 [doi]

Fairness for Workers Who Pull the Arms: An Index Based Policy for Allocation of Restless Bandit TasksArpita Biswas, Jackson A. Killian, Paula Rodriguez Diaz, Susobhan Ghosh, Milind Tambe. atal 2023: 1321-1328 [doi]

Predicting micronutrient deficiency with publicly available satellite dataElizabeth Bondi-Kelly, Haipeng Chen 0001, Christopher D. Golden, Nikhil Behari, Milind Tambe. aim, 44(1):30-40, March 2023. [doi]

Accounting for Uncertainty in Deceptive Signaling for CybersecurityEdward A. Cranford, Han-Ching Ou, Cleotilde Gonzalez, Milind Tambe, Christian Lebiere. hicss 2023: 876-885 [doi]

Limited Resource Allocation in a Non-Markovian World: The Case of Maternal and Child HealthcarePanayiotis Danassis, Shresth Verma, Jackson A. Killian, Aparna Taneja, Milind Tambe. IJCAI 2023: 5950-5958 [doi]

AI-driven Prices for Externalities and Sustainability in Production MarketsPanayiotis Danassis, Aris Filos-Ratsikas, Haipeng Chen 0001, Milind Tambe, Boi Faltings. atal 2023: 2463-2465 [doi]

Flexible Budgets in Restless Bandits: A Primal-Dual Algorithm for Efficient Budget AllocationPaula Rodriguez Diaz, Jackson A. Killian, Lily Xu, Arun Sai Suggala, Aparna Taneja, Milind Tambe. AAAI 2023: 12103-12111 [doi]

Indexability is Not Enough for Whittle: Improved, Near-Optimal Algorithms for Restless BanditsAbheek Ghosh, Dheeraj Nagaraj, Manish Jain, Milind Tambe. atal 2023: 1294-1302 [doi]

Find Rhinos without Finding Rhinos: Active Learning with Multimodal Imagery of South African Rhino HabitatsLucia Gordon, Nikhil Behari, Samuel Collier, Elizabeth Bondi-Kelly, Jackson A. Killian, Catherine Ressijac, Peter Boucher, Andrew Davies, Milind Tambe. IJCAI 2023: 5977-5985 [doi]

Modeling Robustness in Decision-Focused Learning as a Stackelberg GameSonja Johnson-Yu, Kai Wang 0040, Jessie Finocchiaro, Aparna Taneja, Milind Tambe. atal 2023: 2908-2909 [doi]

Robust Planning over Restless Groups: Engagement Interventions for a Large-Scale Maternal Telehealth ProgramJackson A. Killian, Arpita Biswas, Lily Xu, Shresth Verma, Vineet Nair, Aparna Taneja, Aparna Hegde, Neha Madhiwalla, Paula Rodriguez Diaz, Sonja Johnson-Yu, Milind Tambe. AAAI 2023: 14295-14303 [doi]

Improved Policy Evaluation for Randomized Trials of Algorithmic Resource AllocationAditya Mate, Bryan Wilder, Aparna Taneja, Milind Tambe. icml 2023: 24198-24213 [doi]

Increasing Impact of Mobile Health Programs: SAHELI for Maternal and Child CareShresth Verma, Gargi Singh, Aditya Mate, Paritosh Verma, Sruthi Gorantla, Neha Madhiwalla, Aparna Hegde, Divy Thakkar, Manish Jain, Milind Tambe, Aparna Taneja. AAAI 2023: 15594-15602 [doi]

Restless Multi-Armed Bandits for Maternal and Child Health: Results from Decision-Focused LearningShresth Verma, Aditya Mate, Kai Wang 0040, Neha Madhiwalla, Aparna Hegde, Aparna Taneja, Milind Tambe. atal 2023: 1312-1320 [doi]

Expanding impact of mobile health programs: SAHELI for maternal and child careShresth Verma, Gargi Singh, Aditya Mate, Paritosh Verma, Sruthi Gorantla, Neha Madhiwalla, Aparna Hegde, Divy Thakkar, Manish Jain, Milind Tambe, Aparna Taneja. aim, 44(4):363-376, December 2023. [doi]

Scalable Decision-Focused Learning in Restless Multi-Armed Bandits with Application to Maternal and Child HealthKai Wang, Shresth Verma, Aditya Mate, Sanket Shah, Aparna Taneja, Neha Madhiwalla, Aparna Hegde, Milind Tambe. AAAI 2023: 12138-12146 [doi]

2022

Using Public Data to Predict Demand for Mobile Health ClinicsHaipeng Chen 0001, Susobhan Ghosh, Gregory Fan, Nikhil Behari, Arpita Biswas, Mollie Williams, Nancy E. Oriol, Milind Tambe. AAAI 2022: 12461-12467 [doi]

Coordinating Followers to Reach Better Equilibria: End-to-End Gradient Descent for Stackelberg GamesKai Wang 0040, Lily Xu, Andrew Perrault, Michael K. Reiter, Milind Tambe. AAAI 2022: 5219-5227 [doi]

Designing effective masking strategies for cyberdefense through human experimentation and cognitive modelsPalvi Aggarwal, Omkar Thakoor, Shahin Jabbari, Edward A. Cranford, Christian Lebiere, Milind Tambe, Cleotilde Gonzalez. compsec, 117:102671, 2022. [doi]

Micronutrient Deficiency Prediction via Publicly Available Satellite DataElizabeth Bondi, Haipeng Chen 0001, Christopher D. Golden, Nikhil Behari, Milind Tambe. AAAI 2022: 12454-12460 [doi]

Facilitating Human-Wildlife Cohabitation through Conflict PredictionSusobhan Ghosh, Pradeep Varakantham, Aniket Bhatkhande, Tamanna Ahmad, Anish Andheria, Wenjun Li, Aparna Taneja, Divy Thakkar, Milind Tambe. AAAI 2022: 12496-12502 [doi]

Restless and uncertain: Robust policies for restless bandits via deep multi-agent reinforcement learningJackson A. Killian, Lily Xu, Arpita Biswas, Milind Tambe. uai 2022: 990-1000 [doi]

Solving structured hierarchical games using differential backward inductionZun Li, Feiran Jia, Aditya Mate, Shahin Jabbari, Mithun Chakraborty, Milind Tambe, Yevgeniy Vorobeychik. uai 2022: 1107-1117 [doi]

Field Study in Deploying Restless Multi-Armed Bandits: Assisting Non-profits in Improving Maternal and Child HealthAditya Mate, Lovish Madaan, Aparna Taneja, Neha Madhiwalla, Shresth Verma, Gargi Singh, Aparna Hegde, Pradeep Varakantham, Milind Tambe. AAAI 2022: 12017-12025 [doi]

Efficient Algorithms for Finite Horizon and Streaming Restless Multi-Armed Bandit ProblemsAditya S. Mate, Arpita Biswas, Christoph Siebenbrunner, Susobhan Ghosh, Milind Tambe. atal 2022: 880-888 [doi]

ADVISER: AI-Driven Vaccination Intervention Optimiser for Increasing Vaccine Uptake in NigeriaVineet Nair, Kritika Prakash, Michael Wilbur, Aparna Taneja, Corrine Namblard, Oyindamola Adeyemo, Abhishek Dubey, Abiodun Adereni, Milind Tambe, Ayan Mukhopadhyay. IJCAI 2022: 5129-5135 [doi]

Networked Restless Multi-Armed Bandits for Mobile InterventionsHan-Ching Ou, Christoph Siebenbrunner, Jackson A. Killian, Meredith B. Brooks, David Kempe 0001, Yevgeniy Vorobeychik, Milind Tambe. atal 2022: 1001-1009 [doi]

Decision-Focused Learning without Decision-Making: Learning Locally Optimized Decision LossesSanket Shah, Kai Wang 0040, Bryan Wilder, Andrew Perrault, Milind Tambe. nips 2022: [doi]

AI for Social Impact: Results from Deployments for Public Health and ConversationMilind Tambe. kdd 2022: 2 [doi]

Ranked Prioritization of Groups in Combinatorial Bandit AllocationLily Xu, Arpita Biswas, Fei Fang, Milind Tambe. IJCAI 2022: 5206-5212 [doi]

Evolutionary Approach to Security Games with SignalingAdam Zychowski, Jacek Mandziuk, Elizabeth Bondi, Aravind Venugopal, Milind Tambe, Balaraman Ravindran. IJCAI 2022: 620-627 [doi]

2021

Learning MDPs from Features: Predict-Then-Optimize for Sequential Decision Making by Reinforcement LearningKai Wang 0040, Sanket Shah, Haipeng Chen 0001, Andrew Perrault, Finale Doshi-Velez, Milind Tambe. nips 2021: 8795-8806 [doi]

Learn to Intervene: An Adaptive Learning Policy for Restless Bandits in Application to Preventive HealthcareArpita Biswas, Gaurav Aggarwal, Pradeep Varakantham, Milind Tambe. IJCAI 2021: 4039-4046 [doi]

Learning Index Policies for Restless Bandits with Application to Maternal HealthcareArpita Biswas, Gaurav Aggarwal, Pradeep Varakantham, Milind Tambe. atal 2021: 1467-1468 [doi]

Contingency-aware influence maximization: A reinforcement learning approachHaipeng Chen, Wei Qiu 0001, Han-Ching Ou, Bo An 0001, Milind Tambe. uai 2021: 1535-1545 [doi]

Towards a Cognitive Theory of Cyber DeceptionEdward A. Cranford, Cleotilde Gonzalez, Palvi Aggarwal, Milind Tambe, Sarah Cooney, Christian Lebiere. cogsci, 45(7), 2021. [doi]

Measuring Data Collection Diligence for Community HealthcareRamesha Karunasena, Mohammad Sarparajul Ambiya, Arunesh Sinha, Ruchit Nagar, Saachi Dalal, Hamid Abdullah, Divy Thakkar, Dhyanesh Narayanan, Milind Tambe. eaamo 2021: [doi]

Q-Learning Lagrange Policies for Multi-Action Restless BanditsJackson A. Killian, Arpita Biswas, Sanket Shah, Milind Tambe. kdd 2021: 871-881 [doi]

Beyond "To Act or Not to Act": Fast Lagrangian Approaches to General Multi-Action Restless BanditsJackson A. Killian, Andrew Perrault, Milind Tambe. atal 2021: 710-718 [doi]

Risk-Aware Interventions in Public Health: Planning with Restless Multi-Armed BanditsAditya Mate, Andrew Perrault, Milind Tambe. atal 2021: 880-888 [doi]

Active Screening for Recurrent Diseases: A Reinforcement Learning ApproachHan-Ching Ou, Haipeng Chen, Shahin Jabbari, Milind Tambe. atal 2021: 992-1000 [doi]

Fair Influence Maximization: a Welfare Optimization ApproachAida Rahmattalabi, Shahin Jabbari, Himabindu Lakkaraju, Phebe Vayanos, Max Izenberg, Ryan Brown, Eric Rice, Milind Tambe. AAAI 2021: 11630-11638 [doi]

Cohorting to Isolate Asymptomatic Spreaders: An Agent-Based Simulation Study on the Mumbai Suburban RailwayAlok Talekar, Sharad Shriram, Nidhin K. Vaidhiyan, Gaurav Aggarwal, Jiangzhuo Chen, Srinivasan Venkatramanan, Lijing Wang 0001, Aniruddha Adiga, Adam Sadilek, Ashish Tendulkar, Madhav Marathe, Rajesh Sundaresan, Milind Tambe. atal 2021: 1680-1682 [doi]

Reinforcement Learning for Unified Allocation and Patrolling in Signaling Games with UncertaintyAravind Venugopal, Elizabeth Bondi, Harshavardhan Kamarthi, Keval Dholakia, Balaraman Ravindran, Milind Tambe. atal 2021: 1353-1361 [doi]

Tracking Disease Outbreaks from Sparse Data with Bayesian InferenceBryan Wilder, Michael J. Mina, Milind Tambe. AAAI 2021: 4883-4891 [doi]

Clinical Trial of an AI-Augmented Intervention for HIV Prevention in Youth Experiencing HomelessnessBryan Wilder, Laura Onasch-Vera, Graham DiGuiseppi, Robin Petering, Chyna Hill, Amulya Yadav, Eric Rice, Milind Tambe. AAAI 2021: 14948-14956 [doi]

Allocating outreach resources for disease control in a dynamic population with information spreadBryan Wilder, Sze-Chuan Suen, Milind Tambe. iiset, 53(6):629-642, 2021. [doi]

Robust reinforcement learning under minimax regret for green securityLily Xu, Andrew Perrault, Fei Fang, Haipeng Chen, Milind Tambe. uai 2021: 257-267 [doi]

Dual-Mandate Patrols: Multi-Armed Bandits for Green SecurityLily Xu, Elizabeth Bondi, Fei Fang, Andrew Perrault, Kai Wang 0040, Milind Tambe. AAAI 2021: 14974-14982 [doi]

2020

Automatically Learning Compact Quality-aware Surrogates for Optimization ProblemsKai Wang 0040, Bryan Wilder, Andrew Perrault, Milind Tambe. nips 2020: [doi]

Robust Lock-Down Optimization for COVID-19 Policy GuidanceAnkit Bhardwaj, Han-Ching Ou, Haipeng Chen 0001, Shahin Jabbari, Milind Tambe, Rahul Panicker, Alpan Raval. aaaifs 2021: [doi]

BIRDSAI: A Dataset for Detection and Tracking in Aerial Thermal Infrared VideosElizabeth Bondi, Raghav Jain, Palash Aggrawal, Saket Anand, Robert Hannaford, Ashish Kapoor, Jim Piavis, Shital Shah, Lucas Joppa, Bistra Dilkina, Milind Tambe. wacv 2020: 1736-1745 [doi]

To Signal or Not To Signal: Exploiting Uncertain Real-Time Information in Signaling Games for Security and SustainabilityElizabeth Bondi, Hoon Oh, Haifeng Xu, Fei Fang, Bistra Dilkina, Milind Tambe. AAAI 2020: 1369-1377 [doi]

Adaptive Cyber Deception: Cognitively Informed Signaling for Cyber DefenseEdward A. Cranford, Cleotilde Gonzalez, Palvi Aggarwal, Sarah Cooney, Milind Tambe, Christian Lebiere. hicss 2020: 1-10 [doi]

Toward Personalized Deceptive Signaling for Cyber Defense Using Cognitive ModelsEdward A. Cranford, Cleotilde Gonzalez, Palvi Aggarwal, Sarah Cooney, Milind Tambe, Christian Lebiere. topics, 12(3):992-1011, 2020. [doi]

MIPaaL: Mixed Integer Program as a LayerAaron Ferber, Bryan Wilder, Bistra Dilkina, Milind Tambe. AAAI 2020: 1504-1511 [doi]

Influence Maximization in Unknown Social Networks: Learning Policies for Effective Graph SamplingHarshavardhan Kamarthi, Priyesh Vijayan, Bryan Wilder, Balaraman Ravindran, Milind Tambe. atal 2020: 575-583 [doi]

Collapsing Bandits and Their Application to Public Health InterventionAditya Mate, Jackson A. Killian, Haifeng Xu, Andrew Perrault, Milind Tambe. nips 2020: [doi]

Robust Spatial-Temporal Incident PredictionAyan Mukhopadhyay, Kai Wang, Andrew Perrault, Mykel J. Kochenderfer, Milind Tambe, Yevgeniy Vorobeychik. uai 2020: 155 [doi]

Who and When to Screen: Multi-Round Active Screening for Network Recurrent Infectious Diseases Under UncertaintyHan-Ching Ou, Arunesh Sinha, Sze-Chuan Suen, Andrew Perrault, Alpan Raval, Milind Tambe. atal 2020: 992-1000 [doi]

Active Screening on Recurrent Diseases Contact Networks with Uncertainty: A Reinforcement Learning ApproachHan-Ching Ou, Kai Wang 0040, Finale Doshi-Velez, Milind Tambe. mabs 2021: 54-65 [doi]

End-to-End Game-Focused Learning of Adversary Behavior in Security GamesAndrew Perrault, Bryan Wilder, Eric Ewing, Aditya Mate, Bistra Dilkina, Milind Tambe. AAAI 2020: 1378-1386 [doi]

Artificial Intelligence for Social Impact: Learning and Planning in the Data-to-Deployment PipelineAndrew Perrault, Fei Fang, Arunesh Sinha, Milind Tambe. aim, 41(4):3-16, 2020. [doi]

Game Theoretic Cyber Deception to Foil Adversarial Network ReconnaissanceAaron Schlenker, Omkar Thakoor, Haifeng Xu, Fei Fang, Milind Tambe, Phebe Vayanos. In Sushil Jajodia, George Cybenko, V. S. Subrahmanian, Vipin Swarup, Cliff Wang, Michael P. Wellman, editors, Adaptive Autonomous Secure Cyber Systems. pages 183-204, Springer, 2020. [doi]

Solving Online Threat Screening Games using Constrained Action Space Reinforcement LearningSanket Shah, Arunesh Sinha, radeep Varakanthamp, Andrew Perrault, Milind Tambe. AAAI 2020: 2226-2235 [doi]

Exploiting Bounded Rationality in Risk-Based Cyber Camouflage GamesOmkar Thakoor, Shahin Jabbari, Palvi Aggarwal, Cleotilde Gonzalez, Milind Tambe, Phebe Vayanos. GameSec 2020: 103-124 [doi]

Scalable Game-Focused Learning of Adversary Models: Data-to-Decisions in Network Security GamesKai Wang, Andrew Perrault, Aditya Mate, Milind Tambe. atal 2020: 1449-1457 [doi]

Stay Ahead of Poachers: Illegal Wildlife Poaching Prediction and Patrol Planning Under Uncertainty with Field Test Evaluations (Short Version)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. icde 2020: 1898-1901 [doi]

Modeling the dynamism of HIV information diffusion in multiplex networks of homeless youthLindsay E. Young, Jerome R. Mayaud, Sze-Chuan Suen, Milind Tambe, Eric Rice. socnet, 63:112-121, 2020. [doi]

2019

Broken Signals in Security Games: Coordinating Patrollers and Sensors in the Real WorldElizabeth Bondi, Hoon Oh, Haifeng Xu, Fei Fang, Bistra Dilkina, Milind Tambe. atal 2019: 1838-1840 [doi]

Using Game Theory in Real Time in the Real World: A Conservation Case StudyElizabeth Bondi, Hoon Oh, Haifeng Xu, Fei Fang, Bistra Dilkina, Milind Tambe. atal 2019: 2336-2338 [doi]

Warning Time: Optimizing Strategic Signaling for Security Against Boundedly Rational AdversariesSarah Cooney, Phebe Vayanos, Thanh Hong Nguyen, Cleotilde Gonzalez, Christian Lebiere, Edward A. Cranford, Milind Tambe. atal 2019: 1892-1894 [doi]

Mobile Game Theory with Street GangsSarah Cooney, Wendy Gomez, Kai Wang, Jorja Leap, P. Jeffrey Brantingham, Milind Tambe. pkdd 2020: 579-589 [doi]

Learning to Signal in the Goldilocks Zone: Improving Adversary Compliance in Security GamesSarah Cooney, Kai Wang, Elizabeth Bondi, Thanh Hong Nguyen, Phebe Vayanos, Hailey Winetrobe, Edward A. Cranford, Cleotilde Gonzalez, Christian Lebiere, Milind Tambe. pkdd 2020: 725-740 [doi]

Don't Put All Your Strategies in One Basket: Playing Green Security Games with Imperfect Prior KnowledgeShahrzad Gholami, Amulya Yadav, Long Tran-Thanh, Bistra Dilkina, Milind Tambe. atal 2019: 395-403 [doi]

On the Inducibility of Stackelberg Equilibrium for Security GamesQingyu Guo, Jiarui Gan, Fei Fang, Long Tran-Thanh, Milind Tambe, Bo An. AAAI 2019: 2020-2028 [doi]

Deep Fictitious Play for Games with Continuous Action SpacesNitin Kamra, Umang Gupta, Kai Wang, Fei Fang, Yan Liu, Milind Tambe. atal 2019: 2042-2044 [doi]

DeepFP for Finding Nash Equilibrium in Continuous Action SpacesNitin Kamra, Umang Gupta, Kai Wang, Fei Fang, Yan Liu 0002, Milind Tambe. GameSec 2019: 238-258 [doi]

Learning to Prescribe Interventions for Tuberculosis Patients Using Digital Adherence DataJackson A. Killian, Bryan Wilder, Amit Sharma, Vinod Choudhary, Bistra Dilkina, Milind Tambe. kdd 2019: 2430-2438 [doi]

Exploring Algorithmic Fairness in Robust Graph Covering ProblemsAida Rahmattalabi, Phebe Vayanos, Anthony Fulginiti, Eric Rice, Bryan Wilder, Amulya Yadav, Milind Tambe. nips 2019: 15750-15761 [doi]

Robust Peer-Monitoring on Graphs with an Application to Suicide Prevention in Social NetworksAida Rahmattalabi, Phebe Vayanos, Anthony Fulginiti, Milind Tambe. atal 2019: 2168-2170 [doi]

General-Sum Cyber Deception Games under Partial Attacker Valuation InformationOmkar Thakoor, Milind Tambe, Phebe Vayanos, Haifeng Xu, Christopher Kiekintveld. atal 2019: 2215-2217 [doi]

Cyber Camouflage Games for Strategic DeceptionOmkar Thakoor, Milind Tambe, Phebe Vayanos, Haifeng Xu, Christopher Kiekintveld, Fei Fang. GameSec 2019: 525-541 [doi]

Group-Fairness in Influence MaximizationAlan Tsang, Bryan Wilder, Eric Rice, Milind Tambe, Yair Zick. IJCAI 2019: 5997-6005 [doi]

When Players Affect Target Values: Modeling and Solving Dynamic Partially Observable Security GamesXinrun Wang, Milind Tambe, Branislav Bosanský, Bo An. GameSec 2019: 542-562 [doi]

Improving GP-UCB Algorithm by Harnessing Decomposed FeedbackKai Wang, Bryan Wilder, Sze-Chuan Suen, Bistra Dilkina, Milind Tambe. pkdd 2020: 555-569 [doi]

Melding the Data-Decisions Pipeline: Decision-Focused Learning for Combinatorial OptimizationBryan Wilder, Bistra Dilkina, Milind Tambe. AAAI 2019: 1658-1665 [doi]

End to end learning and optimization on graphsBryan Wilder, Eric Ewing, Bistra Dilkina, Milind Tambe. nips 2019: 4674-4685 [doi]

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