Reconciling explanations for the evolution of evolvability. - Bryan Wilder; Kenneth O. Stanley (Adapt. Behav., 2015)

SPECTRE: A Game Theoretic Framework for Preventing Collusion in Security Games (Demonstration). - Shahrzad Gholami; Bryan Wilder; Matthew Brown 002; Arunesh Sinha; Nicole D. Sintov; Milind Tambe (AAMAS, 2016)

Toward Addressing Collusion Among Human Adversaries in Security Games. - Shahrzad Gholami; Bryan Wilder; Matthew Brown 002; Dana Thomas; Nicole D. Sintov; Milind Tambe (ECAI, 2016)

Divide to Defend: Collusive Security Games. - Shahrzad Gholami; Bryan Wilder; Matthew Brown 002; Dana Thomas; Nicole D. Sintov; Milind Tambe (GameSec, 2016)

On the Critical Role of Divergent Selection in Evolvability. - Joel Lehman; Bryan Wilder; Kenneth O. Stanley (Frontiers Robotics AI, 2016)

Uncharted but not Uninfluenced: Influence Maximization with an Uncertain Network. - Bryan Wilder; Amulya Yadav; Nicole Immorlica; Eric Rice; Milind Tambe (AAMAS, 2017)

Influence Maximization in the Field: The Arduous Journey from Emerging to Deployed Application. - Amulya Yadav; Bryan Wilder; Eric Rice; Robin Petering; Jaih Craddock; Amanda Yoshioka-Maxwell; Mary Hemler; Laura Onasch-Vera; Milind Tambe; Darlene Woo (AAMAS, 2017)

Influence Maximization with an Unknown Network by Exploiting Community Structure. - Bryan Wilder; Nicole Immorlica; Eric Rice; Milind Tambe (SocInf@IJCAI, 2017)

AI in Informal Science Education: Bringing Turing Back to Life to Perform the Turing Test. - Avelino J. Gonzalez; James Hollister; Ronald F. DeMara; Jason Leigh; Brandan Lanman; Sangyoon Lee 007; Shane T. Parker; Christopher Walls; Jeanne E. Parker; Josiah Wong; Clayton Barham; Bryan Wilder (Int. J. Artif. Intell. Educ., 2017)

Activating the "Breakfast Club": Modeling Influence Spread in Natural-World Social Networks. - Lily Hu; Bryan Wilder; Amulya Yadav; Eric Rice; Milind Tambe (CoRR, 2017)

Equilibrium computation for zero sum games with submodular structure. - Bryan Wilder (CoRR, 2017)

Remembering a Conversation - A Conversational Memory Architecture for Embodied Conversational Agents. - Miguel Elvir; Avelino J. Gonzalez; Christopher Walls; Bryan Wilder (J. Intell. Syst., 2017)

Equilibrium Computation and Robust Optimization in Zero Sum Games With Submodular Structure. - Bryan Wilder (AAAI, 2018)

Risk-Sensitive Submodular Optimization. - Bryan Wilder (AAAI, 2018)

Maximizing Influence in an Unknown Social Network. - Bryan Wilder; Nicole Immorlica; Eric Rice; Milind Tambe (AAAI, 2018)

Preventing Infectious Disease in Dynamic Populations Under Uncertainty. - Bryan Wilder; Sze-Chuan Suen; Milind Tambe (AAAI, 2018)

Utilizing Housing Resources for Homeless Youth Through the Lens of Multiple Multi-Dimensional Knapsacks. - Hau Chan; Long Tran-Thanh; Bryan Wilder; Eric Rice; Phebe Vayanos; Milind Tambe (AIES, 2018)

Activating the: Modeling Influence Spread in Natural-World Social Networks. - Lily Hu; Bryan Wilder; Amulya Yadav; Eric Rice; Milind Tambe (AAMAS, 2018)

End-to-End Influence Maximization in the Field. - Bryan Wilder; Laura Onasch-Vera; Juliana Hudson; Jose Luna; Nicole Wilson; Robin Petering; Darlene Woo; Milind Tambe; Eric Rice (AAMAS, 2018)

Optimizing Network Structure for Preventative Health. - Bryan Wilder; Han-Ching Ou; Kayla de la Haye; Milind Tambe (AAMAS, 2018)

Controlling Elections through Social Influence. - Bryan Wilder; Yevgeniy Vorobeychik (AAMAS, 2018)

Designing Fair, Efficient, and Interpretable Policies for Prioritizing Homeless Youth for Housing Resources. - Mohammad Javad Azizi; Phebe Vayanos; Bryan Wilder; Eric Rice; Milind Tambe (CPAIOR, 2018)

Algorithmic Social Intervention. - Bryan Wilder (IJCAI, 2018)

End to end influence maximization for HIV prevention. - Bryan Wilder; Laura Onasch-Vera; Juliana Hudson; Jose Luna; Nicole Wilson; Robin Petering; Darlene Woo; Milind Tambe; Eric Rice (AIH@IJCAI, 2018)

Bridging the Gap Between Theory and Practice in Influence Maximization: Raising Awareness about HIV among Homeless Youth. - Amulya Yadav; Bryan Wilder; Eric Rice; Robin Petering; Jaih Craddock; Amanda Yoshioka-Maxwell; Mary Hemler; Laura Onasch-Vera; Milind Tambe; Darlene Woo (IJCAI, 2018)

Melding the Data-Decisions Pipeline: Decision-Focused Learning for Combinatorial Optimization. - Bryan Wilder; Bistra Dilkina; Milind Tambe (AAAI, 2019)

Defending Elections against Malicious Spread of Misinformation. - Bryan Wilder; Yevgeniy Vorobeychik (AAAI, 2019)

Distributionally Robust Submodular Maximization. - Matthew Staib; Bryan Wilder; Stefanie Jegelka (AISTATS, 2019)

SATNet: Bridging deep learning and logical reasoning using a differentiable satisfiability solver. - Po-Wei Wang; Priya L. Donti; Bryan Wilder; J. Zico Kolter (ICML, 2019)

Group-Fairness in Influence Maximization. - Alan Tsang; Bryan Wilder; Eric Rice; Milind Tambe; Yair Zick (IJCAI, 2019)

AI at the Margins: Data, Decisions, and Inclusive Social Impact. - Bryan Wilder (IJCAI, 2019)

Learning to Prescribe Interventions for Tuberculosis Patients Using Digital Adherence Data. - Jackson A. Killian; Bryan Wilder; Amit Sharma 007; Vinod Choudhary; Bistra Dilkina; Milind Tambe (KDD, 2019)

Exploring Algorithmic Fairness in Robust Graph Covering Problems. - Aida Rahmattalabi; Phebe Vayanos; Anthony Fulginiti; Eric Rice; Bryan Wilder; Amulya Yadav; Milind Tambe (NeurIPS, 2019)

End to end learning and optimization on graphs. - Bryan Wilder; Eric Ewing; Bistra Dilkina; Milind Tambe (NeurIPS, 2019)

Improving GP-UCB Algorithm by Harnessing Decomposed Feedback. - Kai Wang 040; Bryan Wilder; Sze-Chuan Suen; Bistra Dilkina; Milind Tambe (PKDD/ECML Workshops (1), 2019)

Decision-Focused Learning of Adversary Behavior in Security Games. - Andrew Perrault; Bryan Wilder; Eric Ewing; Aditya Mate; Bistra Dilkina; Milind Tambe (CoRR, 2019)

Learning policies for Social network discovery with Reinforcement learning. - Harshavardhan Kamarthi; Priyesh Vijayan; Bryan Wilder; Balaraman Ravindran; Milind Tambe (CoRR, 2019)

MIPaaL: Mixed Integer Program as a Layer. - Aaron M. Ferber; Bryan Wilder; Bistra Dilkina; Milind Tambe (AAAI, 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 (AAAI, 2020)

Influence Maximization in Unknown Social Networks: Learning Policies for Effective Graph Sampling. - Harshavardhan Kamarthi; Priyesh Vijayan; Bryan Wilder; Balaraman Ravindran; Milind Tambe (AAMAS, 2020)

Learning to Complement Humans. - Bryan Wilder; Eric Horvitz; Ece Kamar (IJCAI, 2020)

Automatically Learning Compact Quality-aware Surrogates for Optimization Problems. - Kai Wang 040; Bryan Wilder; Andrew Perrault; Milind Tambe (NeurIPS, 2020)

Fuzzy c-Means Clustering for Persistence Diagrams. - Thomas O. M. Davies; Jack Aspinall; Bryan Wilder; Long Tran-Thanh (CoRR, 2020)

Preliminary Results from a Peer-Led, Social Network Intervention, Augmented by Artificial Intelligence to Prevent HIV among Youth Experiencing Homelessness. - Eric Rice; Laura Onasch-Vera; Graham T. DiGuiseppi; Bryan Wilder; Robin Petering; Chyna Hill; Amulya Yadav; Milind Tambe (CoRR, 2020)

Tracking Disease Outbreaks from Sparse Data with Bayesian Inference. - Bryan Wilder; Michael J. Mina; Milind Tambe (AAAI, 2021)

Clinical Trial of an AI-Augmented Intervention for HIV Prevention in Youth Experiencing Homelessness. - Bryan Wilder; Laura Onasch-Vera; Graham T. DiGuiseppi; Robin Petering; Chyna Hill; Amulya Yadav; Eric Rice; Milind Tambe (AAAI, 2021)

End-to-End Constrained Optimization Learning: A Survey. - James Kotary; Ferdinando Fioretto; Pascal Van Hentenryck; Bryan Wilder (IJCAI, 2021)

Harnessing Heterogeneity: Learning from Decomposed Feedback in Bayesian Modeling. - Kai Wang 040; Bryan Wilder; Sze-Chuan Suen; Bistra Dilkina; Milind Tambe (CoRR, 2021)

Allocating outreach resources for disease control in a dynamic population with information spread. - Bryan Wilder; Sze-Chuan Suen; Milind Tambe (IISE Trans., 2021)

Fuzzy c-means clustering in persistence diagram space for deep learning model selection. - Thomas Davies 001; Jack Aspinall; Bryan Wilder; Tran-Thanh Long (NeurReps, 2022)

Decision-Focused Learning without Decision-Making: Learning Locally Optimized Decision Losses. - Sanket Shah; Kai Wang 040; Bryan Wilder; Andrew Perrault; Milind Tambe (NeurIPS, 2022)

Learning (Local) Surrogate Loss Functions for Predict-Then-Optimize Problems. - Sanket Shah; Bryan Wilder; Andrew Perrault; Milind Tambe (CoRR, 2022)

AI for Equitable, Data-Driven Decisions in Public Health. - Bryan Wilder (AAAI, 2023)

Ideal Abstractions for Decision-Focused Learning. - Michael Poli; Stefano Massaroli; Stefano Ermon; Bryan Wilder; Eric Horvitz (AISTATS, 2023)

A Learning Approach to Complex Contagion Influence Maximization. - Haipeng Chen 001; Bryan Wilder; Wei Qiu 001; Bo An 001; Eric Rice; Milind Tambe (AAMAS, 2023)

Improved Policy Evaluation for Randomized Trials of Algorithmic Resource Allocation. - Aditya Mate; Bryan Wilder; Aparna Taneja; Milind Tambe (ICML, 2023)

Complex Contagion Influence Maximization: A Reinforcement Learning Approach. - Haipeng Chen 001; Bryan Wilder; Wei Qiu 001; Bo An 001; Eric Rice; Milind Tambe (IJCAI, 2023)

Computationally Assisted Quality Control for Public Health Data Streams. - Ananya Joshi 001; Kathryn Mazaitis; Roni Rosenfeld; Bryan Wilder (IJCAI, 2023)

Auditing Fairness by Betting. - Ben Chugg; Santiago Cortes-Gomez; Bryan Wilder; Aaditya Ramdas (NeurIPS, 2023)

Inference under constrained distribution shifts. - Santiago Cortes-Gomez; Mateo Dulce Rubio; Bryan Wilder (CoRR, 2023)

Report on the 2nd ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO 2022). - Elena Falcettoni; Dina Machuve; Bryan Wilder; Angela Zhou (SIGecom Exch., 2023)

Outlier Ranking for Large-Scale Public Health Data. - Ananya Joshi 001; Tina Townes; Nolan Gormley; Luke Neureiter; Roni Rosenfeld; Bryan Wilder (AAAI, 2024)

Leaving the Nest: Going beyond Local Loss Functions for Predict-Then-Optimize. - Sanket Shah; Bryan Wilder; Andrew Perrault; Milind Tambe (AAAI, 2024)

Auditing Fairness under Unobserved Confounding. - Yewon Byun; Dylan Sam; Michael Oberst; Zachary C. Lipton; Bryan Wilder (AISTATS, 2024)

Statistical Inference Under Constrained Selection Bias. - Santiago Cortes-Gomez; Mateo Dulce Rubio; Carlos Miguel Patiño; Bryan Wilder (ICML, 2024)

Decision-Focused Evaluation of Worst-Case Distribution Shift. - Kevin Ren; Yewon Byun; Bryan Wilder (UAI, 2024)

Outlier Ranking in Large-Scale Public Health Streams. - Ananya Joshi 001; Tina Townes; Nolan Gormley; Luke Neureiter; Roni Rosenfeld; Bryan Wilder (CoRR, 2024)

Orthogonal Causal Calibration. - Justin Whitehouse; Christopher Jung 001; Vasilis Syrgkanis; Bryan Wilder; Zhiwei Steven Wu (CoRR, 2024)

Preliminary Study of the Impact of AI-Based Interventions on Health and Behavioral Outcomes in Maternal Health Programs. - Arpan Dasgupta; Niclas Boehmer; Neha Madhiwalla; Aparna Hedge; Bryan Wilder; Milind Tambe; Aparna Taneja (CoRR, 2024)

Decision-Focused Uncertainty Quantification. - Santiago Cortes-Gomez; Carlos Miguel Patiño; Yewon Byun; Steven Wu 001; Eric Horvitz; Bryan Wilder (CoRR, 2024)

Data-driven Design of Randomized Control Trials with Guaranteed Treatment Effects. - Santiago Cortes-Gomez; Naveen Raman 001; Aarti Singh; Bryan Wilder (CoRR, 2024)

Accounting for Missing Covariates in Heterogeneous Treatment Estimation. - Khurram Yamin; Vibhhu Sharma; Edward Kennedy; Bryan Wilder (CoRR, 2024)

Failure Modes of LLMs for Causal Reasoning on Narratives. - Khurram Yamin; Shantanu Gupta; Gaurav R. Ghosal; Zachary C. Lipton; Bryan Wilder (CoRR, 2024)

Generate to Discriminate: Expert Routing for Continual Learning. - Yewon Byun; Sanket Vaibhav Mehta; Saurabh Garg; Emma Strubell; Michael Oberst; Bryan Wilder; Zachary C. Lipton (CoRR, 2024)

Orthogonal Causal Calibration (Extended Abstract). - Justin Whitehouse; Christopher Jung 001; Vasilis Syrgkanis; Bryan Wilder; Zhiwei Steven Wu (COLT, 2025)

Utility-Directed Conformal Prediction: A Decision-Aware Framework for Actionable Uncertainty Quantification. - Santiago Cortes-Gomez; Carlos Miguel Patiño; Yewon Byun; Steven Wu 001; Eric Horvitz; Bryan Wilder (ICLR, 2025)

Comparing Targeting Strategies for Maximizing Social Welfare with Limited Resources. - Vibhhu Sharma; Bryan Wilder (ICLR, 2025)

Reinforcement learning with combinatorial actions for coupled restless bandits. - Lily Xu; Bryan Wilder; Elias Boutros Khalil; Milind Tambe (ICLR, 2025)

Learning treatment effects while treating those in need. - Bryan Wilder; Pim Welle (EC, 2025)

Dependent Randomized Rounding for Budget Constrained Experimental Design. - Khurram Yamin; Edward Kennedy; Bryan Wilder (UAI, 2025)

The Next Wave of AI for Social Impact: Challenges and Opportunities. - Milind Tambe; Fei Fang 001; Andrew Perrault; Bryan Wilder (IEEE Intell. Syst., 2025)

Federated epidemic surveillance. - Ruiqi Lyu; Roni Rosenfeld; Bryan Wilder (PLoS Comput. Biol., 2025)

Nowcasting reported covid-19 hospitalizations using de-identified, aggregated medical insurance claims data. - Xueda Shen; Aaron Rumack; Bryan Wilder; Ryan J. Tibshirani (PLoS Comput. Biol., 2025)

Explaining Concept Shift with Interpretable Feature Attribution. - Ruiqi Lyu; Alistair Turcan; Bryan Wilder (CoRR, 2025)

An AI-Based Public Health Data Monitoring System. - Ananya Joshi 001; Nolan Gormley; Richa Gadgil; Tina Townes; Roni Rosenfeld; Bryan Wilder (CoRR, 2025)

LLMs Struggle to Perform Counterfactual Reasoning with Parametric Knowledge. - Khurram Yamin; Gaurav R. Ghosal; Bryan Wilder (CoRR, 2025)

Bridging Prediction and Intervention Problems in Social Systems. - Lydia T. Liu; Inioluwa Deborah Raji; Angela Zhou; Luke Guerdan; Jessica Hullman; Daniel Malinsky; Bryan Wilder; Simone Zhang; Hammaad Adam; Amanda Coston; Benjamin Laufer; Ezinne Nwankwo; et al. (CoRR, 2025)

Using Imperfect Synthetic Data in Downstream Inference Tasks. - Yewon Byun; Shantanu Gupta; Zachary C. Lipton; Rachel Leah Childers; Bryan Wilder (CoRR, 2025)