Structural Stability of a Family of Group Formation Games, C. Wang, M. Moharrami, K. Jin, D. Kempe, P. J. Brantingham, and M. Liu. IEEE Conference on Decision and Control (CDC). (to appear December 2021)
Multi-planner intervention in network games with community structures, K. Jin and M. Liu, IEEE Conference on Decision and Control (CDC). (to appear December 2021)
PATHATTACK: Attacking Shortest Paths in Complex Networks, Benjamin Miller, Zohair Shafi, Wheeler Ruml, Yevgeniy Vorobeychik, Tina Eliassi-Rad and Scott Alfeld, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2021. (to appear, Sept 2021)
Altruism Design in Networked Public Goods Games. International Joint Conference on Artificial Intelligence, Sixie Yu, David Kempe, and Yevgeniy Vorobeychik, August 2021.
Q-Learning Lagrange Policies for Multi-Action Restless Bandits, Jackson A. Killian, Arpita Biswas, Sanket Shah, Milind Tambe. Proceedings of the 27th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, August 2021.
Contingency-Aware Influence Maximization: A Reinforcement Learning Approach, Haipeng Chen, Wei Qiu, Han-Ching Ou, Bo An, and Milind Tambe. Conference on Uncertainty in Artificial Intelligence, 7/25/2021.
Beyond To Act or Not to Act: Fast Lagrangian Approaches to General Multi-Action Restless Bandits, Jackson A. Killian, Andrew Perrault, Milind Tambe. 20th International Conference on Autonomous Agents and Multiagent Systems. 2021 May
Designing Contracts for Trading Private and Heterogeneous Data Using a Biased Differentially Private Algorithm, M. Khalili, X. Zhang, and M. Liu, IEEE Access, April 2021.
Multi-Scale Games: Representing and Solving Games on Networks with Group Structure, K. Jin, Y. Vorobeychik, and M. Liu, Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI- 21), February 2021.
Dual-Mandate Patrols: Multi-Armed Bandits for Green Security, Lily Xu, Elizabeth Bondi, Fei Fang, Andrew Perrault, Kai Wang, and Milind Tambe. Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21), 2021.
Active Screening for Recurrent Diseases: A Reinforcement Learning Approach, Han-Ching Ou, Haipeng Chen, Shahin Jabbari, and Milind Tambe. 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS). London, UK, 2021.
A Game-Theoretic Approach for Hierarchical Policy-Making, Feiran Jia, Aditya Mate, Zun Li, Shahin Jabbari, Mithun Chakraborty, Milind Tambe, Michael Wellman, and Yevgeniy Vorobeychik. 2nd International (Virtual) Workshop on Autonomous Agents for Social Good (AASG 2021)
Learning Opportunistic Adversarial Model on Global Wildlife Trade, Kai Wang, Jeffrey Brantingham, and Milind Tambe. AAMAS Autonomous Agents for Social Good Workshop (AASG), 2021.
Clinical trial of an AI-augmented intervention for HIV prevention in youth experiencing homelessness, Bryan Wilder, Laura Onasch-Vera, Graham Diguiseppi, Robin Petering, Chyna Hill, Amulya Yadav, Eric Rice, and Milind Tambe. AAAI Conference on Artificial Intelligence, 2021.
Tracking disease outbreaks from sparse data with Bayesian inference, Bryan Wilder, Michael Mina, and Milind Tambe. AAAI Conference on Artificial Intelligence, 2021.
Test sensitivity is secondary to frequency and turnaround time for COVID-19 screening, Daniel B. Larremore, Bryan Wilder, Evan Lester, Soraya Shehata, James M. Burke, James A. Hay, Milind Tambe, Michael J. Mina, and Roy Parker. Science Advances, November 2020.
Modeling between-population variation in COVID-19 dynamics in Hubei, Lombardy, and New York City, Bryan Wilder, Marie Charpignon, Jackson A Killian, Han-Ching Ou, Aditya Mate, Shahin Jabbari, Andrew Perrault, Angel Desai, Milind Tambe, and Maimuna S. Majumder. Proceedings of the National Academy of Sciences, 9/24/2020.
Risk-Aware Interventions in Public Health: Planning with Restless Multi-Armed Bandits, Aditya Mate, Andrew Perrault, Milind Tambe. 20th International Conference on Autonomous Agents and Multiagent Systems, May 2021.
Robust Reinforcement Learning Under Minimax Regret for Green Security, Lily Xu, Andrew Perrault, Fei Fang, Haipeng Chen, and Milind Tambe. Conference on Uncertainty in Artificial Intelligence, 2021.
Robust Coordination in Adversarial Social Networks: From Human Behavior to Agent-Based Modeling, Chen Hajaj, Zlatko Joveski, Sixie Yu, and Yevgeniy Vorobeychik., Network Science, 2021. [PDF]
FACESEC: A Fine-grained Robustness Evaluation Framework for Face Recognition Systems, Liang Tong, Zhengzhang Chen, Jingchao Ni, Wei Cheng, Dongjin Song, Haifeng Chen, and Yevgeniy Vorobeychik, Conference on Computer Vision and Pattern Recognition, 2021. [PDF]
Strategic Evasion of Centrality Measures. International Conference on Autonomous Agents and Multiagent Systems, Marcin Waniek, Jan Woznica, Kai Zhou, Yevgeniy Vorobeychik, Talal Rahwan and Tomasz Michalak, 2021. [PDF]
POTION: Optimizing Graph Structure for Targeted Diffusion. Sixie Yu, Leo Torres, Scott Alfeld, Tina Eliassi-Rad, Yevgeniy Vorobeychik, SIAM International Conference on Data Mining, 2021.
Collapsing Bandits and Their Application to Public Health Intervention, Aditya Mate, Jackson A. Killian, Haifeng Xu, Andrew Perrault, Milind Tambe. Neural Information Processing Systems (NeurIPS), 2020.
Automatically Learning Compact Quality-aware Surrogates for Optimization Problems, Kai Wang, Bryan Wilder, Andrew Perrault, and Milind Tambe. Advances in Neural Information Processing Systems 33 (NeurIPS 2020), 2020. Spotlight presentation.
Gang-related crime in Los Angeles remained stable following COVID-19 social distancing orders, Brantingham, P.J., Tita, G.E., Mohler G. Criminology & Public Policy, 2021. [PDF]
Public Cooperation and the Police: Do Calls-For-Service Increase After Homicides? Brantingham, P.J., and Uchida, C.D., Journal of Criminal Justice. 73:101785, March-April 2021. [PDF]
Resource Pooling for Shared Fate: Incentivizing Effort in Inter- dependent Security Games through Cross-investments, M. Khalili, X. Zhang, and M. Liu, IEEE Transactions on Control of Network Systems (TCNS), December 2020.
Blocking Adversarial Influence in Social Networks, Feiran Jia, Kai Zhou, Charles Kamhoua, and Yevgeniy Vorobeychik, Conference on Decision and Game Theory for Security, 2020.
Inducing Equilibria in Networked Public Goods Games through Network Structure Modification, David Kempe, Sixie Yu, and Yevgeniy Vorobeychik, International Conference on Autonomous Agents and Multiagent Systems, 2020.
Is Gang Violent Crime More Contagious than Non-gang Violent Crime? 2020. Brantingham,P.J., Yuan, B., and Herz, D., Journal of Quantitative Criminology, September 2020.
A Game-Theoretic Approach for Hierarchical Policy-Making, Feiran Jia, Aditya Mate, Zun Li, Shahin Jabbari, Mithun Chakraborty, Milind Tambe, Michael Wellman and Yevgeniy Vorobeychik, 2nd International (Virtual) Workshop on Autonomous Agents for Social Good, AASG 2021.
Resource Pooling for Shared Fate: Incentivizing Effort in Interdependent Security Games through Cross-investments, Mohammadmahdi Khalili, Xueru Zhang, and Mingyan Liu, IEEE Transactions on Control of Network Systems (TCNS), December, 2020.
Robust Spatial-Temporal Incident Prediction, Ayan Mukhopadhyay, Kai Wang, Andrew Perrault, Mykel Kochenderfer, Milind Tambe, Yevgeniy Vorobeychik, Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020.
Stay Ahead of Poachers: Illegal Wildlife Poaching Prediction and Patrol Planning Under Uncertainty with Field Test Evaluations, Lily Xu, Shahrzad Gholami, Sara McCarthy, Bistra Dilkina, Andrew Plumptre, Milind Tambe, Rohit Singh, Mustapha Nsubuga, Joshua Mabonga, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba, Tom Okello, Eric Enyel, 36th IEEE International Conference on Data Engineering (ICDE), 2020.
Scalable Game-Focused Learning of Adversary Models: Data-to-Decisions in Network Security Games, Kai Wang, Andrew Perrault, Aditya Mate, Milind Tambe, International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), 2020.
Who and When to Screen: Multi-Round Active Screening for Network Recurrent Infectious Diseases Under Uncertainty, Han-Ching Ou, Arunesh Sinha, Sze-Chuan Suen, Andrew Perrault, Alpan Raval, Milind Tambe, International Conference on Autonomous Agents and Multi-Agent Systems ( AAMAS), 2020.
End-to-End Game-Focused Learning of Adversary Behavior in Security Games, Andrew Perrault, Bryan Wilder, Eric Ewing, Aditya Mate, Bistra Dilkina, Milind Tambe, Thirty-fourth AAAI Conference on Artificial Intelligence, 2020.
MIPaaL: Mixed Integer Program as a Layer, Aaron Ferber, Bryan Wilder, Bistra Dilkina, Milind Tambe, Thirty-fourth AAAI Conference on Artificial Intelligence, 2020.
End to end learning and optimization on graphs, Bryan Wilder, Eric Ewing, Bistra Dilkina, Milind Tambe, Thirty-third Conference on Neural Information Processing Systems (NeurIPS), 2019.
Impact of Social Distancing During Covid-19 Pandemic on Crime in Los Angeles and Indianapolis, Mohler, George and Bertozzi, Andrea L. and Carter, Jeremy and Short, Martin B. and Sledge, Daniel and Tita, George E. and Uchida, Craig D. and Brantingham, P. Jeffrey, Journal of Criminal Justice, vol. 68, pp. 101692, 2020.
Fitting in and breaking up: A nonlinear version of coevolving voter models, Yacoub H. Kureh and Mason A. Porter, Physical Review E, 101 (6), pp. 062303-062325, June 2020.
Robust Spatial-Temporal Incident Prediction, Ayan Mukhopadhyay, Kai Wang, Andrew Perrault, Mykel Kochenderfer, Milind Tambe, and Yevgeniy Vorobeychik, Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR volume 124, 2020.
Robust Collective Classification against Structural Attacks, Kai Zhou and Yevgeniy Vorobeychik, Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR volume 124, 2020.
Defending Against Physically Realizable Attacks on Image Classification, Tong Wu, Liang Tong, and Yevgeniy Vorobeychik, International Conference on Learning Representations (ICLR), 2020.
Deception through half-truths, Andrew Estornell, Sanmay Das, and Yevgeniy Vorobeychik, AAAI Conference on Artificial Intelligence, 2020.
Computing equilibria in binary networked public goods games, Sixie Yu, Kai Zhou, Jeffrey Brantingham, and Yevgeniy Vorobeychik, AAAI Conference on Artificial Intelligence, 2020.
Adversarial Robustness of Similarity-Based Link Prediction, Kai Zhou, Tomasz Michalak, and Yevgeniy Vorobeychik, IEEE International Conference on Data Mining (ICDM), 2019.
Approximation Algorithms for Coordinating Ad Campaigns on Social Networks, Kartik Lakhotia and David Kempe, ACM International Conference on Information and Knowledge Management (CIKM), 2019.
Interactive Learning of a Dynamic Structure, Ehsan Emamjomeh-Zadeh, David Kempe, Mohammad Mahdian, Rob Schapire, International Conference on Algorithmic Learning Theory (ALT), 2020.
Games on Networks with Community Structure: Existence, Uniqueness and Stability of Equilibria, Kun Jin, Mohammadmahdi Khalili, and Mingyan Liu, American Control Conference (ACC), July 2020.
Structure learning for approximate solution of many-player games, Zun Li and Michael P. Wellman, 34th AAAI Conference on Artificial Intelligence, February 2020.
Melding the data-decisions pipeline: Decision-focused learning for combinatorial optimization, Bryan Wilder, Bistra Dilkina, and Milind Tambe. Proceedings of the Association for the Advancement of Artificial Intelligence (AAAI) Conference, 2019.
Don’t Put All Your Strategies in One Basket: Playing Green Security Games with Imperfect Prior Knowledge, Shahrzad Gholami, Amulya Yadav, Long Tran-Thanh, Bistra Dilkina, and Milind Tambe, Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, Pp. 395–403, 2019.
Deep Fictitious Play for Games with Continuous Action Spaces, Nitin Kamra, Umang Gupta, Kai Wang, Fei Fang, Yan Liu, and Milind Tambe, “Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems,” Pp. 2042–2044, 2019.
Learning to Prescribe Interventions for Tuberculosis Patients, Jackson A. Killian, Bryan Wilder, Amit Sharma, Vinod Choudhary, Bistra Dilkina, and Milind Tambe, ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD-19), 2019.
Integrating optimization and learning to prescribe interventions for tuberculosis patients, Bryan Wilder, Jackson A. Killian, Amit Sharma, Vinod Choudhary, Bistra Dilkina, and Milind Tambe, 10th International Workshop on Optimization in Multiagent Systems (OptMAS), 2019.
Group-Fairness in Influence Maximization, Alan Tsang, Bryan Wilder, Eric Rice, Milind Tambe, and Yair Zick, International Joint Conference on Artificial Intelligence,” 2019. [PDF]
Attacking Similarity-Based Link Prediction in Social Networks, Kai Zhou, Tomasz P. Michalak, Talal Rahwan, Marcin Waniek, Yevgeniy Vorobeychik, Proc. of the 18th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2019), May 2019.
Incentivizing Collaboration in a Competition, Arunesh Sinha, Michael P. Wellman, Proc. of the 18th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2019), May 2019.
Removing Malicious Nodes from Networks, Sixie Yu, Yevgeniy Vorobeychik, Proc. of the 18th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2019), May 2019.
Generative Graph Models based on Laplacian Spectra, Alana Shine, David Kempe, International World Wide Web Conference Committee, May 2019.
Defending Elections Against Malicious Spread of Misinformation, Bryan Wilder, Yevgeniy Vorobeychik, Association for the Advancement of Artificial Intelligence (AAAI), January 2019.