Wilder, Bryan

49 publications

TMLR 2026 Accounting for Missing Covariates in Heterogeneous Treatment Estimation Khurram Yamin, Vibhhu Sharma, Edward Kennedy, Bryan Wilder

ICLR 2025 Comparing Targeting Strategies for Maximizing Social Welfare with Limited Resources Vibhhu Sharma, Bryan Wilder

ICML 2025 Data-Driven Design of Randomized Control Trials with Guaranteed Treatment Effects Santiago Cortes-Gomez, Naveen Janaki Raman, Aarti Singh, Bryan Wilder

UAI 2025 Dependent Randomized Rounding for Budget Constrained Experimental Design Khurram Yamin, Edward Kennedy, Bryan Wilder

NeurIPS 2025 Distributionally Robust Feature Selection Maitreyi Swaroop, Tamar Krishnamurti, Bryan Wilder

TMLR 2025 Expert Routing with Synthetic Data for Domain Incremental Learning Yewon Byun, Sanket Vaibhav Mehta, Saurabh Garg, Emma Strubell, Michael Oberst, Bryan Wilder, Zachary Chase Lipton

NeurIPS 2025 Fostering the Ecosystem of AI for Social Impact Requires Expanding and Strengthening Evaluation Standards Bryan Wilder, Angela Zhou

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

ICLR 2025 Reinforcement Learning with Combinatorial Actions for Coupled Restless Bandits Lily Xu, Bryan Wilder, Elias Boutros Khalil, Milind Tambe

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

NeurIPS 2025 Valid Inference with Imperfect Synthetic Data Yewon Byun, Shantanu Gupta, Zachary Chase Lipton, Rachel Leah Childers, Bryan Wilder

AISTATS 2024 Auditing Fairness Under Unobserved Confounding Yewon Byun, Dylan Sam, Michael Oberst, Zachary Lipton, Bryan Wilder

UAI 2024 Decision-Focused Evaluation of Worst-Case Distribution Shift Kevin Ren, Yewon Byun, 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 Outlier Ranking for Large-Scale Public Health Data Ananya Joshi, Tina Townes, Nolan Gormley, Luke Neureiter, Roni Rosenfeld, Bryan Wilder

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

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

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

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

IJCAI 2023 Computationally Assisted Quality Control for Public Health Data Streams Ananya Joshi, Kathryn Mazaitis, Roni Rosenfeld, Bryan Wilder

ICMLW 2023 Conditional Diffusion Replay for Continual Learning in Medical Settings Yewon Byun, Saurabh Garg, Sanket Vaibhav Mehta, Praveer Singh, Jayashree Kalpathy-cramer, Bryan Wilder, Zachary Chase Lipton

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

ICMLW 2023 Identifying Inequity in Treatment Allocation Yewon Byun, Dylan Sam, Zachary Chase Lipton, Bryan Wilder

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

NeurIPS 2022 Decision-Focused Learning Without Decision-Making: Learning Locally Optimized Decision Losses Sanket Shah, Kai Wang, Bryan Wilder, Andrew Perrault, Milind Tambe

NeurIPSW 2022 Fuzzy C-Means Clustering in Persistence Diagram Space for Deep Learning Model Selection Thomas Davies, Jack Aspinall, Bryan Wilder, Long Tran-Thanh

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

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

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

NeurIPS 2020 Automatically Learning Compact Quality-Aware Surrogates for Optimization Problems Kai Wang, Bryan Wilder, Andrew Perrault, 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

NeurIPSW 2020 Fuzzy C-Means Clustering for Persistence Diagrams Thomas Davies, Jack Aspinall, Bryan Wilder, Long Tran-Thanh

IJCAI 2020 Learning to Complement Humans Bryan Wilder, Eric Horvitz, Ece Kamar

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

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

AAAI 2019 Defending Elections Against Malicious Spread of Misinformation Bryan Wilder, Yevgeniy Vorobeychik

AISTATS 2019 Distributionally Robust Submodular Maximization Matthew Staib, Bryan Wilder, Stefanie Jegelka

NeurIPS 2019 End to End Learning and Optimization on Graphs Bryan Wilder, Eric Ewing, Bistra Dilkina, Milind Tambe

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

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

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

ICML 2019 SATNet: Bridging Deep Learning and Logical Reasoning Using a Differentiable Satisfiability Solver Po-Wei Wang, Priya Donti, Bryan Wilder, Zico Kolter

IJCAI 2018 Algorithmic Social Intervention Bryan Wilder

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 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

AAAI 2018 Equilibrium Computation and Robust Optimization in Zero Sum Games with Submodular Structure 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 Risk-Sensitive Submodular Optimization Bryan Wilder