Bryan Wilder

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 91

Top Topics

Bayesian Modeling

Infectious Disease

Reinforcement Learning

Top Venues

Publications

Bryan Wilder, Pim Welle
Learning treatment effects while treating those in need. CoRR (2024)
Justin Whitehouse, Christopher Jung, Vasilis Syrgkanis, Bryan Wilder, Zhiwei Steven Wu
Orthogonal Causal Calibration. CoRR (2024)
Yewon Byun, Dylan Sam, Michael Oberst, Zachary C. Lipton, Bryan Wilder
Auditing Fairness under Unobserved Confounding. AISTATS (2024)
Sanket Shah, Bryan Wilder, Andrew Perrault, Milind Tambe
Leaving the Nest: Going beyond Local Loss Functions for Predict-Then-Optimize. AAAI (2024)
Arpan Dasgupta, Niclas Boehmer, Neha Madhiwalla, Aparna Hedge, Bryan Wilder, Milind Tambe, Aparna Taneja
Preliminary Study of the Impact of AI-Based Interventions on Health and Behavioral Outcomes in Maternal Health Programs. CoRR (2024)
Kevin Ren, Yewon Byun, Bryan Wilder
Decision-Focused Evaluation of Worst-Case Distribution Shift. CoRR (2024)
Ananya Joshi, Tina Townes, Nolan Gormley, Luke Neureiter, Roni Rosenfeld, Bryan Wilder
Outlier Ranking for Large-Scale Public Health Data. AAAI (2024)
Yewon Byun, Dylan Sam, Michael Oberst, Zachary C. Lipton, Bryan Wilder
Auditing Fairness under Unobserved Confounding. CoRR (2024)
Ananya Joshi, Tina Townes, Nolan Gormley, Luke Neureiter, Roni Rosenfeld, Bryan Wilder
Outlier Ranking in Large-Scale Public Health Streams. CoRR (2024)
Bryan Wilder
AI for Equitable, Data-Driven Decisions in Public Health. AAAI (2023)
Ben Chugg, Santiago Cortes-Gomez, Bryan Wilder, Aaditya Ramdas
Auditing Fairness by Betting. CoRR (2023)
Michael Poli, Stefano Massaroli, Stefano Ermon, Bryan Wilder, Eric Horvitz
Ideal Abstractions for Decision-Focused Learning. AISTATS (2023)
Ananya Joshi, Kathryn Mazaitis, Roni Rosenfeld, Bryan Wilder
Computationally Assisted Quality Control for Public Health Data Streams. CoRR (2023)
Haipeng Chen, Bryan Wilder, Wei Qiu, Bo An, Eric Rice, Milind Tambe
Complex Contagion Influence Maximization: A Reinforcement Learning Approach. IJCAI (2023)
Ruiqi Lyu, Bryan Wilder, Roni Rosenfeld
Federated Epidemic Surveillance. CoRR (2023)
Aditya Mate, Bryan Wilder, Aparna Taneja, Milind Tambe
Improved Policy Evaluation for Randomized Trials of Algorithmic Resource Allocation. CoRR (2023)
Aditya Mate, Bryan Wilder, Aparna Taneja, Milind Tambe
Improved Policy Evaluation for Randomized Trials of Algorithmic Resource Allocation. ICML (2023)
Sanket Shah, Andrew Perrault, Bryan Wilder, Milind Tambe
Leaving the Nest: Going Beyond Local Loss Functions for Predict-Then-Optimize. CoRR (2023)
Santiago Cortes-Gomez, Mateo Dulce, Bryan Wilder
Inference under constrained distribution shifts. CoRR (2023)
Ben Chugg, Santiago Cortes-Gomez, Bryan Wilder, Aaditya Ramdas
Auditing Fairness by Betting. NeurIPS (2023)
Ananya Joshi, Kathryn Mazaitis, Roni Rosenfeld, Bryan Wilder
Computationally Assisted Quality Control for Public Health Data Streams. IJCAI (2023)
Michael Poli, Stefano Massaroli, Stefano Ermon, Bryan Wilder, Eric Horvitz
Ideal Abstractions for Decision-Focused Learning. CoRR (2023)
Haipeng Chen, Bryan Wilder, Wei Qiu, Bo An, Eric Rice, Milind Tambe
A Learning Approach to Complex Contagion Influence Maximization. AAMAS (2023)
Thomas Davies, Jack Aspinall, Bryan Wilder, Tran-Thanh Long
Fuzzy c-means clustering in persistence diagram space for deep learning model selection. NeurReps (2022)
Sanket Shah, Kai Wang, Bryan Wilder, Andrew Perrault, Milind Tambe
Decision-Focused Learning without Decision-Making: Learning Locally Optimized Decision Losses. NeurIPS (2022)
Sanket Shah, Bryan Wilder, Andrew Perrault, Milind Tambe
Learning (Local) Surrogate Loss Functions for Predict-Then-Optimize Problems. CoRR (2022)
James Kotary, Ferdinando Fioretto, Pascal Van Hentenryck, Bryan Wilder
End-to-End Constrained Optimization Learning: A Survey. CoRR (2021)
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)
James Kotary, Ferdinando Fioretto, Pascal Van Hentenryck, Bryan Wilder
End-to-End Constrained Optimization Learning: A Survey. IJCAI (2021)
Bryan Wilder, Michael J. Mina, Milind Tambe
Tracking Disease Outbreaks from Sparse Data with Bayesian Inference. AAAI (2021)
Kai Wang, Bryan Wilder, Sze-Chuan Suen, Bistra Dilkina, Milind Tambe
Harnessing Heterogeneity: Learning from Decomposed Feedback in Bayesian Modeling. CoRR (2021)
Bryan Wilder, Sze-Chuan Suen, Milind Tambe
Allocating outreach resources for disease control in a dynamic population with information spread. IISE Trans. 53 (6) (2021)
Thomas O. M. Davies, Jack Aspinall, Bryan Wilder, Long Tran-Thanh
Fuzzy c-Means Clustering for Persistence Diagrams. CoRR (2020)
Bryan Wilder, Eric Horvitz, Ece Kamar
Learning to Complement Humans. CoRR (2020)
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 (2020)
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)
Aida Rahmattalabi, Phebe Vayanos, Anthony Fulginiti, Eric Rice, Bryan Wilder, Amulya Yadav, Milind Tambe
Exploring Algorithmic Fairness in Robust Graph Covering Problems. CoRR (2020)
Aaron M. Ferber, Bryan Wilder, Bistra Dilkina, Milind Tambe
MIPaaL: Mixed Integer Program as a Layer. AAAI (2020)
Harshavardhan Kamarthi, Priyesh Vijayan, Bryan Wilder, Balaraman Ravindran, Milind Tambe
Influence Maximization in Unknown Social Networks: Learning Policies for Effective Graph Sampling. AAMAS (2020)
Kai Wang, Bryan Wilder, Andrew Perrault, Milind Tambe
Automatically Learning Compact Quality-aware Surrogates for Optimization Problems. NeurIPS (2020)
Bryan Wilder, Eric Horvitz, Ece Kamar
Learning to Complement Humans. IJCAI (2020)
Bryan Wilder, Michael J. Mina, Milind Tambe
Tracking disease outbreaks from sparse data with Bayesian inference. CoRR (2020)
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 (2020)
Kai Wang, Bryan Wilder, Andrew Perrault, Milind Tambe
Automatically Learning Compact Quality-aware Surrogates for Optimization Problems. CoRR (2020)
Aaron M. Ferber, Bryan Wilder, Bistra Dilkina, Milind Tambe
MIPaaL: Mixed Integer Program as a Layer. CoRR (2019)
Jackson A. Killian, Bryan Wilder, Amit Sharma, Vinod Choudhary, Bistra Dilkina, Milind Tambe
Learning to Prescribe Interventions for Tuberculosis Patients using Digital Adherence Data. CoRR (2019)
Bryan Wilder, Bistra Dilkina, Milind Tambe
Melding the Data-Decisions Pipeline: Decision-Focused Learning for Combinatorial Optimization. AAAI (2019)
Po-Wei Wang, Priya L. Donti, Bryan Wilder, J. Zico Kolter
SATNet: Bridging deep learning and logical reasoning using a differentiable satisfiability solver. ICML (2019)
Bryan Wilder, Yevgeniy Vorobeychik
Defending Elections against Malicious Spread of Misinformation. AAAI (2019)
Bryan Wilder
AI at the Margins: Data, Decisions, and Inclusive Social Impact. IJCAI (2019)
Andrew Perrault, Bryan Wilder, Eric Ewing, Aditya Mate, Bistra Dilkina, Milind Tambe
Decision-Focused Learning of Adversary Behavior in Security Games. CoRR (2019)
Bryan Wilder, Eric Ewing, Bistra Dilkina, Milind Tambe
End to end learning and optimization on graphs. NeurIPS (2019)
Kai Wang, Bryan Wilder, Sze-Chuan Suen, Bistra Dilkina, Milind Tambe
Improving GP-UCB Algorithm by Harnessing Decomposed Feedback. PKDD/ECML Workshops (1) (2019)
Matthew Staib, Bryan Wilder, Stefanie Jegelka
Distributionally Robust Submodular Maximization. AISTATS (2019)
Alan Tsang, Bryan Wilder, Eric Rice, Milind Tambe, Yair Zick
Group-Fairness in Influence Maximization. IJCAI (2019)
Po-Wei Wang, Priya L. Donti, Bryan Wilder, J. Zico Kolter
SATNet: Bridging deep learning and logical reasoning using a differentiable satisfiability solver. CoRR (2019)
Alan Tsang, Bryan Wilder, Eric Rice, Milind Tambe, Yair Zick
Group-Fairness in Influence Maximization. CoRR (2019)
Bryan Wilder, Eric Ewing, Bistra Dilkina, Milind Tambe
End to end learning and optimization on graphs. CoRR (2019)
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)
Harshavardhan Kamarthi, Priyesh Vijayan, Bryan Wilder, Balaraman Ravindran, Milind Tambe
Learning policies for Social network discovery with Reinforcement learning. CoRR (2019)
Aida Rahmattalabi, Phebe Vayanos, Anthony Fulginiti, Eric Rice, Bryan Wilder, Amulya Yadav, Milind Tambe
Exploring Algorithmic Fairness in Robust Graph Covering Problems. NeurIPS (2019)
Bryan Wilder
Risk-Sensitive Submodular Optimization. AAAI (2018)
Bryan Wilder, Laura Onasch-Vera, Juliana Hudson, Jose Luna, Nicole Wilson, Robin Petering, Darlene Woo, Milind Tambe, Eric Rice
End-to-End Influence Maximization in the Field. AAMAS (2018)
Mohammad Javad Azizi, Phebe Vayanos, Bryan Wilder, Eric Rice, Milind Tambe
Designing Fair, Efficient, and Interpretable Policies for Prioritizing Homeless Youth for Housing Resources. CPAIOR (2018)
Bryan Wilder
Equilibrium Computation and Robust Optimization in Zero Sum Games With Submodular Structure. AAAI (2018)
Hau Chan, Long Tran-Thanh, Bryan Wilder, Eric Rice, Phebe Vayanos, Milind Tambe
Utilizing Housing Resources for Homeless Youth Through the Lens of Multiple Multi-Dimensional Knapsacks. AIES (2018)
Matthew Staib, Bryan Wilder, Stefanie Jegelka
Distributionally Robust Submodular Maximization. CoRR (2018)
Bryan Wilder, Yevgeniy Vorobeychik
Controlling Elections through Social Influence. AAMAS (2018)
Bryan Wilder
Algorithmic Social Intervention. IJCAI (2018)
Bryan Wilder, Laura Onasch-Vera, Juliana Hudson, Jose Luna, Nicole Wilson, Robin Petering, Darlene Woo, Milind Tambe, Eric Rice
End to end influence maximization for HIV prevention. AIH@IJCAI (2018)
Bryan Wilder, Nicole Immorlica, Eric Rice, Milind Tambe
Maximizing Influence in an Unknown Social Network. AAAI (2018)
Lily Hu, Bryan Wilder, Amulya Yadav, Eric Rice, Milind Tambe
Activating the: Modeling Influence Spread in Natural-World Social Networks. AAMAS (2018)
Bryan Wilder, Han-Ching Ou, Kayla de la Haye, Milind Tambe
Optimizing Network Structure for Preventative Health. AAMAS (2018)
Bryan Wilder, Sze-Chuan Suen, Milind Tambe
Preventing Infectious Disease in Dynamic Populations Under Uncertainty. AAAI Workshops (2018)
Amulya Yadav, Bryan Wilder, Eric Rice, Robin Petering, Jaih Craddock, Amanda Yoshioka-Maxwell, Mary Hemler, Laura Onasch-Vera, Milind Tambe, Darlene Woo
Bridging the Gap Between Theory and Practice in Influence Maximization: Raising Awareness about HIV among Homeless Youth. IJCAI (2018)
Bryan Wilder, Sze-Chuan Suen, Milind Tambe
Preventing Infectious Disease in Dynamic Populations Under Uncertainty. AAAI (2018)
Bryan Wilder
Algorithmic Social Intervention. CoRR (2018)
Bryan Wilder, Bistra Dilkina, Milind Tambe
Melding the Data-Decisions Pipeline: Decision-Focused Learning for Combinatorial Optimization. CoRR (2018)
Bryan Wilder, Yevgeniy Vorobeychik
Defending Elections Against Malicious Spread of Misinformation. CoRR (2018)
Avelino J. Gonzalez, James Hollister, Ronald F. DeMara, Jason Leigh, Brandan Lanman, Sangyoon Lee, Shane T. Parker, Christopher Walls, Jeanne E. Parker, Josiah Wong, Clayton Barham, Bryan Wilder
AI in Informal Science Education: Bringing Turing Back to Life to Perform the Turing Test. Int. J. Artif. Intell. Educ. 27 (2) (2017)
Bryan Wilder, Nicole Immorlica, Eric Rice, Milind Tambe
Influence Maximization with an Unknown Network by Exploiting Community Structure. SocInf@IJCAI (2017)
Miguel Elvir, Avelino J. Gonzalez, Christopher Walls, Bryan Wilder
Remembering a Conversation - A Conversational Memory Architecture for Embodied Conversational Agents. J. Intell. Syst. 26 (1) (2017)
Lily Hu, Bryan Wilder, Amulya Yadav, Eric Rice, Milind Tambe
Activating the "Breakfast Club": Modeling Influence Spread in Natural-World Social Networks. CoRR (2017)
Amulya Yadav, Bryan Wilder, Eric Rice, Robin Petering, Jaih Craddock, Amanda Yoshioka-Maxwell, Mary Hemler, Laura Onasch-Vera, Milind Tambe, Darlene Woo
Influence Maximization in the Field: The Arduous Journey from Emerging to Deployed Application. AAMAS (2017)
Bryan Wilder, Yevgeniy Vorobeychik
Controlling Elections through Social Influence. CoRR (2017)
Bryan Wilder, Amulya Yadav, Nicole Immorlica, Eric Rice, Milind Tambe
Uncharted but not Uninfluenced: Influence Maximization with an Uncertain Network. AAMAS (2017)
Bryan Wilder
Equilibrium computation for zero sum games with submodular structure. CoRR (2017)
Shahrzad Gholami, Bryan Wilder, Matthew Brown, Arunesh Sinha, Nicole D. Sintov, Milind Tambe
SPECTRE: A Game Theoretic Framework for Preventing Collusion in Security Games (Demonstration). AAMAS (2016)
Shahrzad Gholami, Bryan Wilder, Matthew Brown, Dana Thomas, Nicole D. Sintov, Milind Tambe
Divide to Defend: Collusive Security Games. GameSec (2016)
Joel Lehman, Bryan Wilder, Kenneth O. Stanley
On the Critical Role of Divergent Selection in Evolvability. Frontiers Robotics AI 3 (2016)
Shahrzad Gholami, Bryan Wilder, Matthew Brown, Dana Thomas, Nicole D. Sintov, Milind Tambe
Toward Addressing Collusion Among Human Adversaries in Security Games. ECAI (2016)
Bryan Wilder, Kenneth O. Stanley
Reconciling explanations for the evolution of evolvability. Adapt. Behav. 23 (3) (2015)