Bryan Wilder

133 papers A* 37A 15B 1C 1Journal 72Unranked 7
YearRankTypeTitle / Venue / Authors
2026 J jnl
Accounting for Missing Covariates in Heterogeneous Treatment Estimation.
Trans. Mach. Learn. Res.
Khurram Yamin, Vibhhu Sharma, Edward Kennedy, Bryan Wilder
2026 J jnl
Developing and evaluating a chatbot to support maternal health care.
CoRR
Smriti Jha, Vidhi Jain, Jianyu Xu, Grace Liu, Sowmya Ramesh, Jitender Nagpal, Gretchen Chapman, Benjamin Bellows, Siddhartha Goyal, Aarti Singh, Bryan Wilder
2026 J jnl
Do LLMs Act Like Rational Agents? Measuring Belief Coherence in Probabilistic Decision Making.
CoRR
Khurram Yamin, Jingjing Tang, Santiago Cortes-Gomez, Amit Sharma, Eric Horvitz, Bryan Wilder
2026 J jnl
IV Co-Scientist: Multi-Agent LLM Framework for Causal Instrumental Variable Discovery.
CoRR
Ivaxi Sheth, Zhijing Jin, Bryan Wilder, Dominik Janzing, Mario Fritz
2026 A* conf
Reducing Alert Fatigue Through AI Ranking: A Deployed Public Health Data Monitoring System.
AAAI
Ananya Joshi, Nolan Gormley, Richa Gadgil, Catalina Vajiac, Tina Townes, Roni Rosenfeld, Bryan Wilder
2025 J jnl
An AI-Based Public Health Data Monitoring System.
CoRR
Ananya Joshi, Nolan Gormley, Richa Gadgil, Tina Townes, Roni Rosenfeld, Bryan Wilder
2025 J jnl
Bridging Prediction and Intervention Problems in Social Systems.
CoRR
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, Michael Zanger-Tishler, Eli Ben-Michael, Solon Barocas, Avi Feller, Marissa Gerchick, Talia Gillis, Shion Guha, Daniel E. Ho, Lily Hu, Kosuke Imai, Sayash Kapoor, Joshua Loftus, Razieh Nabi, Arvind Narayanan, Ben Recht, Juan Carlos Perdomo, Matthew J. Salganik, Mark P. Sendak, Alexander Tolbert, Berk Ustun, Suresh Venkatasubramanian, Angelina Wang, Ashia Wilson
2025 J jnl
Combining digital data streams and epidemic networks for real time outbreak detection.
CoRR
Ruiqi Lyu, Alistair Turcan, Bryan Wilder
2025 A* conf
Comparing Targeting Strategies for Maximizing Social Welfare with Limited Resources.
ICLR
Vibhhu Sharma, Bryan Wilder
2025 A* conf
Data-driven Design of Randomized Control Trials with Guaranteed Treatment Effects.
ICML
Santiago Cortes-Gomez, Naveen Janaki Raman, Aarti Singh, Bryan Wilder
2025 A conf
Dependent Randomized Rounding for Budget Constrained Experimental Design.
UAI
Khurram Yamin, Edward Kennedy, Bryan Wilder
2025 J jnl
Dependent Randomized Rounding for Budget Constrained Experimental Design.
CoRR
Khurram Yamin, Edward Kennedy, Bryan Wilder
2025 J jnl
Distributionally Robust Feature Selection.
CoRR
Maitreyi Swaroop, Tamar Krishnamurti, Bryan Wilder
2025 J jnl
Expert Routing with Synthetic Data for Domain Incremental Learning.
Trans. Mach. Learn. Res.
Yewon Byun, Sanket Vaibhav Mehta, Saurabh Garg, Emma Strubell, Michael Oberst, Bryan Wilder, Zachary Chase Lipton
2025 J jnl
Explaining Concept Shift with Interpretable Feature Attribution.
CoRR
Ruiqi Lyu, Alistair Turcan, Bryan Wilder
2025 J jnl
Federated epidemic surveillance.
PLoS Comput. Biol.
Ruiqi Lyu, Roni Rosenfeld, Bryan Wilder
2025 J jnl
Fostering the Ecosystem of AI for Social Impact Requires Expanding and Strengthening Evaluation Standards.
CoRR
Bryan Wilder, Angela Zhou
2025 J jnl
Improving constraint-based discovery with robust propagation and reliable LLM priors.
CoRR
Ruiqi Lyu, Alistair Turcan, Martin Jinye Zhang, Bryan Wilder
2025 J jnl
LLMs Struggle to Perform Counterfactual Reasoning with Parametric Knowledge.
CoRR
Khurram Yamin, Gaurav R. Ghosal, Bryan Wilder
2025 A* conf
Learning treatment effects while treating those in need.
EC
Bryan Wilder, Pim Welle
2025 J jnl
Nowcasting reported covid-19 hospitalizations using de-identified, aggregated medical insurance claims data.
PLoS Comput. Biol.
Xueda Shen, Aaron Rumack, Bryan Wilder, Ryan J. Tibshirani
2025 J jnl
OEUVRE: OnlinE Unbiased Variance-Reduced loss Estimation.
CoRR
Kanad Pardeshi, Bryan Wilder, Aarti Singh
2025 J jnl
Online Decision Making with Generative Action Sets.
CoRR
Jianyu Xu, Vidhi Jain, Bryan Wilder, Aarti Singh
2025 A* conf
Orthogonal Causal Calibration (Extended Abstract).
COLT
Justin Whitehouse, Christopher Jung, Vasilis Syrgkanis, Bryan Wilder, Zhiwei Steven Wu
2025 — conf
Predicting Language Models' Success at Zero-Shot Probabilistic Prediction.
EMNLP (Findings)
Kevin Ren, Santiago Cortes-Gomez, Carlos Miguel Patiño, Ananya Joshi, Ruiqi Lyu, Jingjing Tang, Alistair Turcan, Khurram Yamin, Steven Wu, Bryan Wilder
2025 J jnl
Predicting Language Models' Success at Zero-Shot Probabilistic Prediction.
CoRR
Kevin Ren, Santiago Cortes-Gomez, Carlos Miguel Patiño, Ananya Joshi, Ruiqi Lyu, Jingjing Tang, Alistair Turcan, Khurram Yamin, Steven Wu, Bryan Wilder
2025 J jnl
Real-time forecasting of data revisions in epidemic surveillance streams.
PLoS Comput. Biol.
Jingjing Tang, Aaron Rumack, Bryan Wilder, Roni Rosenfeld
2025 A* conf
Reinforcement learning with combinatorial actions for coupled restless bandits.
ICLR
Lily Xu, Bryan Wilder, Elias Boutros Khalil, Milind Tambe
2025 J jnl
Reinforcement learning with combinatorial actions for coupled restless bandits.
CoRR
Lily Xu, Bryan Wilder, Elias B. Khalil, Milind Tambe
2025 J jnl
The Next Wave of AI for Social Impact: Challenges and Opportunities.
IEEE Intell. Syst.
Milind Tambe, Fei Fang, Andrew Perrault, Bryan Wilder
2025 J jnl
Using Imperfect Synthetic Data in Downstream Inference Tasks.
CoRR
Yewon Byun, Shantanu Gupta, Zachary C. Lipton, Rachel Leah Childers, Bryan Wilder
2025 A* conf
Utility-Directed Conformal Prediction: A Decision-Aware Framework for Actionable Uncertainty Quantification.
ICLR
Santiago Cortes-Gomez, Carlos Miguel Patiño, Yewon Byun, Steven Wu, Eric Horvitz, Bryan Wilder
2024 J jnl
Accounting for Missing Covariates in Heterogeneous Treatment Estimation.
CoRR
Khurram Yamin, Vibhhu Sharma, Edward Kennedy, Bryan Wilder
2024 A conf
Auditing Fairness under Unobserved Confounding.
AISTATS
Yewon Byun, Dylan Sam, Michael Oberst, Zachary C. Lipton, Bryan Wilder
2024 J jnl
Auditing Fairness under Unobserved Confounding.
CoRR
Yewon Byun, Dylan Sam, Michael Oberst, Zachary C. Lipton, Bryan Wilder
2024 J jnl
Comparing Targeting Strategies for Maximizing Social Welfare with Limited Resources.
CoRR
Vibhhu Sharma, Bryan Wilder
2024 J jnl
Data-driven Design of Randomized Control Trials with Guaranteed Treatment Effects.
CoRR
Santiago Cortes-Gomez, Naveen Raman, Aarti Singh, Bryan Wilder
2024 A conf
Decision-Focused Evaluation of Worst-Case Distribution Shift.
UAI
Kevin Ren, Yewon Byun, Bryan Wilder
2024 J jnl
Decision-Focused Evaluation of Worst-Case Distribution Shift.
CoRR
Kevin Ren, Yewon Byun, Bryan Wilder
2024 J jnl
Decision-Focused Uncertainty Quantification.
CoRR
Santiago Cortes-Gomez, Carlos Miguel Patiño, Yewon Byun, Steven Wu, Eric Horvitz, Bryan Wilder
2024 J jnl
Failure Modes of LLMs for Causal Reasoning on Narratives.
CoRR
Khurram Yamin, Shantanu Gupta, Gaurav R. Ghosal, Zachary C. Lipton, Bryan Wilder
2024 J jnl
Generate to Discriminate: Expert Routing for Continual Learning.
CoRR
Yewon Byun, Sanket Vaibhav Mehta, Saurabh Garg, Emma Strubell, Michael Oberst, Bryan Wilder, Zachary C. Lipton
2024 J jnl
Learning treatment effects while treating those in need.
CoRR
Bryan Wilder, Pim Welle
2024 A* conf
Leaving the Nest: Going beyond Local Loss Functions for Predict-Then-Optimize.
AAAI
Sanket Shah, Bryan Wilder, Andrew Perrault, Milind Tambe
2024 J jnl
Orthogonal Causal Calibration.
CoRR
Justin Whitehouse, Christopher Jung, Vasilis Syrgkanis, Bryan Wilder, Zhiwei Steven Wu
2024 A* conf
Outlier Ranking for Large-Scale Public Health Data.
AAAI
Ananya Joshi, Tina Townes, Nolan Gormley, Luke Neureiter, Roni Rosenfeld, Bryan Wilder
2024 J jnl
Outlier Ranking in Large-Scale Public Health Streams.
CoRR
Ananya Joshi, Tina Townes, Nolan Gormley, Luke Neureiter, Roni Rosenfeld, Bryan Wilder
2024 J jnl
Preliminary Study of the Impact of AI-Based Interventions on Health and Behavioral Outcomes in Maternal Health Programs.
CoRR
Arpan Dasgupta, Niclas Boehmer, Neha Madhiwalla, Aparna Hegde, Bryan Wilder, Milind Tambe, Aparna Taneja
2024 A* conf
Statistical Inference Under Constrained Selection Bias.
ICML
Santiago Cortes-Gomez, Mateo Dulce Rubio, Carlos Miguel Patiño, Bryan Wilder
2023 A conf
A Learning Approach to Complex Contagion Influence Maximization.
AAMAS
Haipeng Chen, Bryan Wilder, Wei Qiu, Bo An, Eric Rice, Milind Tambe
2023 A* conf
AI for Equitable, Data-Driven Decisions in Public Health.
AAAI
Bryan Wilder
2023 A* conf
Auditing Fairness by Betting.
NeurIPS
Ben Chugg, Santiago Cortes-Gomez, Bryan Wilder, Aaditya Ramdas
2023 J jnl
Auditing Fairness by Betting.
CoRR
Ben Chugg, Santiago Cortes-Gomez, Bryan Wilder, Aaditya Ramdas
2023 A* conf
Complex Contagion Influence Maximization: A Reinforcement Learning Approach.
IJCAI
Haipeng Chen, Bryan Wilder, Wei Qiu, Bo An, Eric Rice, Milind Tambe
2023 A* conf
Computationally Assisted Quality Control for Public Health Data Streams.
IJCAI
Ananya Joshi, Kathryn Mazaitis, Roni Rosenfeld, Bryan Wilder
2023 J jnl
Computationally Assisted Quality Control for Public Health Data Streams.
CoRR
Ananya Joshi, Kathryn Mazaitis, Roni Rosenfeld, Bryan Wilder
2023 J jnl
Federated Epidemic Surveillance.
CoRR
Ruiqi Lyu, Bryan Wilder, Roni Rosenfeld
2023 A conf
Ideal Abstractions for Decision-Focused Learning.
AISTATS
Michael Poli, Stefano Massaroli, Stefano Ermon, Bryan Wilder, Eric Horvitz
2023 J jnl
Ideal Abstractions for Decision-Focused Learning.
CoRR
Michael Poli, Stefano Massaroli, Stefano Ermon, Bryan Wilder, Eric Horvitz
2023 A* conf
Improved Policy Evaluation for Randomized Trials of Algorithmic Resource Allocation.
ICML
Aditya Mate, Bryan Wilder, Aparna Taneja, Milind Tambe
2023 J jnl
Improved Policy Evaluation for Randomized Trials of Algorithmic Resource Allocation.
CoRR
Aditya Mate, Bryan Wilder, Aparna Taneja, Milind Tambe
2023 J jnl
Inference under constrained distribution shifts.
CoRR
Santiago Cortes-Gomez, Mateo Dulce Rubio, Bryan Wilder
2023 J jnl
Leaving the Nest: Going Beyond Local Loss Functions for Predict-Then-Optimize.
CoRR
Sanket Shah, Andrew Perrault, Bryan Wilder, Milind Tambe
2023 J jnl
Report on the 2nd ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO 2022).
SIGecom Exch.
Elena Falcettoni, Dina Machuve, Bryan Wilder, Angela Zhou
2022 A* conf
Decision-Focused Learning without Decision-Making: Learning Locally Optimized Decision Losses.
NeurIPS
Sanket Shah, Kai Wang, Bryan Wilder, Andrew Perrault, Milind Tambe
2022 — conf
Fuzzy c-means clustering in persistence diagram space for deep learning model selection.
NeurReps
Thomas Davies, Jack Aspinall, Bryan Wilder, Tran-Thanh Long
2022 J jnl
Learning (Local) Surrogate Loss Functions for Predict-Then-Optimize Problems.
CoRR
Sanket Shah, Bryan Wilder, Andrew Perrault, Milind Tambe
2021 J jnl
Allocating outreach resources for disease control in a dynamic population with information spread.
IISE Trans.
Bryan Wilder, Sze-Chuan Suen, Milind Tambe
2021 A* conf
Clinical Trial of an AI-Augmented Intervention for HIV Prevention in Youth Experiencing Homelessness.
AAAI
Bryan Wilder, Laura Onasch-Vera, Graham T. DiGuiseppi, Robin Petering, Chyna Hill, Amulya Yadav, Eric Rice, Milind Tambe
2021 A* conf
End-to-End Constrained Optimization Learning: A Survey.
IJCAI
James Kotary, Ferdinando Fioretto, Pascal Van Hentenryck, Bryan Wilder
2021 J jnl
End-to-End Constrained Optimization Learning: A Survey.
CoRR
James Kotary, Ferdinando Fioretto, Pascal Van Hentenryck, Bryan Wilder
2021 J jnl
Harnessing Heterogeneity: Learning from Decomposed Feedback in Bayesian Modeling.
CoRR
Kai Wang, Bryan Wilder, Sze-Chuan Suen, Bistra Dilkina, Milind Tambe
2021 A* conf
Tracking Disease Outbreaks from Sparse Data with Bayesian Inference.
AAAI
Bryan Wilder, Michael J. Mina, Milind Tambe
2020 A* conf
Automatically Learning Compact Quality-aware Surrogates for Optimization Problems.
NeurIPS
Kai Wang, Bryan Wilder, Andrew Perrault, Milind Tambe
2020 J jnl
Automatically Learning Compact Quality-aware Surrogates for Optimization Problems.
CoRR
Kai Wang, Bryan Wilder, Andrew Perrault, Milind Tambe
2020 J jnl
Clinical trial of an AI-augmented intervention for HIV prevention in youth experiencing homelessness.
CoRR
Bryan Wilder, Laura Onasch-Vera, Graham T. DiGuiseppi, Robin Petering, Chyna Hill, Amulya Yadav, Eric Rice, Milind Tambe
2020 A* conf
End-to-End Game-Focused Learning of Adversary Behavior in Security Games.
AAAI
Andrew Perrault, Bryan Wilder, Eric Ewing, Aditya Mate, Bistra Dilkina, Milind Tambe
2020 J jnl
Exploring Algorithmic Fairness in Robust Graph Covering Problems.
CoRR
Aida Rahmattalabi, Phebe Vayanos, Anthony Fulginiti, Eric Rice, Bryan Wilder, Amulya Yadav, Milind Tambe
2020 J jnl
Fuzzy c-Means Clustering for Persistence Diagrams.
CoRR
Thomas O. M. Davies, Jack Aspinall, Bryan Wilder, Long Tran-Thanh
2020 A conf
Influence Maximization in Unknown Social Networks: Learning Policies for Effective Graph Sampling.
AAMAS
Harshavardhan Kamarthi, Priyesh Vijayan, Bryan Wilder, Balaraman Ravindran, Milind Tambe
2020 A* conf
Learning to Complement Humans.
IJCAI
Bryan Wilder, Eric Horvitz, Ece Kamar
2020 J jnl
Learning to Complement Humans.
CoRR
Bryan Wilder, Eric Horvitz, Ece Kamar
2020 A* conf
MIPaaL: Mixed Integer Program as a Layer.
AAAI
Aaron M. Ferber, Bryan Wilder, Bistra Dilkina, Milind Tambe
2020 J jnl
Preliminary Results from a Peer-Led, Social Network Intervention, Augmented by Artificial Intelligence to Prevent HIV among Youth Experiencing Homelessness.
CoRR
Eric Rice, Laura Onasch-Vera, Graham T. DiGuiseppi, Bryan Wilder, Robin Petering, Chyna Hill, Amulya Yadav, Milind Tambe
2020 J jnl
Tracking disease outbreaks from sparse data with Bayesian inference.
CoRR
Bryan Wilder, Michael J. Mina, Milind Tambe
2019 A* conf
AI at the Margins: Data, Decisions, and Inclusive Social Impact.
IJCAI
Bryan Wilder
2019 J jnl
Decision-Focused Learning of Adversary Behavior in Security Games.
CoRR
Andrew Perrault, Bryan Wilder, Eric Ewing, Aditya Mate, Bistra Dilkina, Milind Tambe
2019 A* conf
Defending Elections against Malicious Spread of Misinformation.
AAAI
Bryan Wilder, Yevgeniy Vorobeychik
2019 A conf
Distributionally Robust Submodular Maximization.
AISTATS
Matthew Staib, Bryan Wilder, Stefanie Jegelka
2019 A* conf
End to end learning and optimization on graphs.
NeurIPS
Bryan Wilder, Eric Ewing, Bistra Dilkina, Milind Tambe
2019 J jnl
End to end learning and optimization on graphs.
CoRR
Bryan Wilder, Eric Ewing, Bistra Dilkina, Milind Tambe
2019 A* conf
Exploring Algorithmic Fairness in Robust Graph Covering Problems.
NeurIPS
Aida Rahmattalabi, Phebe Vayanos, Anthony Fulginiti, Eric Rice, Bryan Wilder, Amulya Yadav, Milind Tambe
2019 A* conf
Group-Fairness in Influence Maximization.
IJCAI
Alan Tsang, Bryan Wilder, Eric Rice, Milind Tambe, Yair Zick
2019 J jnl
Group-Fairness in Influence Maximization.
CoRR
Alan Tsang, Bryan Wilder, Eric Rice, Milind Tambe, Yair Zick
2019 — conf
Improving GP-UCB Algorithm by Harnessing Decomposed Feedback.
PKDD/ECML Workshops (1)
Kai Wang, Bryan Wilder, Sze-Chuan Suen, Bistra Dilkina, Milind Tambe
2019 J jnl
Learning policies for Social network discovery with Reinforcement learning.
CoRR
Harshavardhan Kamarthi, Priyesh Vijayan, Bryan Wilder, Balaraman Ravindran, Milind Tambe
2019 A* conf
Learning to Prescribe Interventions for Tuberculosis Patients Using Digital Adherence Data.
KDD
Jackson A. Killian, Bryan Wilder, Amit Sharma, Vinod Choudhary, Bistra Dilkina, Milind Tambe
2019 J jnl
Learning to Prescribe Interventions for Tuberculosis Patients using Digital Adherence Data.
CoRR
Jackson A. Killian, Bryan Wilder, Amit Sharma, Vinod Choudhary, Bistra Dilkina, Milind Tambe
2019 J jnl
MIPaaL: Mixed Integer Program as a Layer.
CoRR
Aaron M. Ferber, Bryan Wilder, Bistra Dilkina, Milind Tambe
2019 A* conf
Melding the Data-Decisions Pipeline: Decision-Focused Learning for Combinatorial Optimization.
AAAI
Bryan Wilder, Bistra Dilkina, Milind Tambe
2019 A* conf
SATNet: Bridging deep learning and logical reasoning using a differentiable satisfiability solver.
ICML
Po-Wei Wang, Priya L. Donti, Bryan Wilder, J. Zico Kolter
2019 J jnl
SATNet: Bridging deep learning and logical reasoning using a differentiable satisfiability solver.
CoRR
Po-Wei Wang, Priya L. Donti, Bryan Wilder, J. Zico Kolter
2018 A conf
Activating the: Modeling Influence Spread in Natural-World Social Networks.
AAMAS
Lily Hu, Bryan Wilder, Amulya Yadav, Eric Rice, Milind Tambe
2018 A* conf
Algorithmic Social Intervention.
IJCAI
Bryan Wilder
2018 J jnl
Algorithmic Social Intervention.
CoRR
Bryan Wilder
2018 A* conf
Bridging the Gap Between Theory and Practice in Influence Maximization: Raising Awareness about HIV among Homeless Youth.
IJCAI
Amulya Yadav, Bryan Wilder, Eric Rice, Robin Petering, Jaih Craddock, Amanda Yoshioka-Maxwell, Mary Hemler, Laura Onasch-Vera, Milind Tambe, Darlene Woo
2018 A conf
Controlling Elections through Social Influence.
AAMAS
Bryan Wilder, Yevgeniy Vorobeychik
2018 J jnl
Defending Elections Against Malicious Spread of Misinformation.
CoRR
Bryan Wilder, Yevgeniy Vorobeychik
2018 B conf
Designing Fair, Efficient, and Interpretable Policies for Prioritizing Homeless Youth for Housing Resources.
CPAIOR
Mohammad Javad Azizi, Phebe Vayanos, Bryan Wilder, Eric Rice, Milind Tambe
2018 J jnl
Distributionally Robust Submodular Maximization.
CoRR
Matthew Staib, Bryan Wilder, Stefanie Jegelka
2018 — conf
End to end influence maximization for HIV prevention.
AIH@IJCAI
Bryan Wilder, Laura Onasch-Vera, Juliana Hudson, Jose Luna, Nicole Wilson, Robin Petering, Darlene Woo, Milind Tambe, Eric Rice
2018 A conf
End-to-End Influence Maximization in the Field.
AAMAS
Bryan Wilder, Laura Onasch-Vera, Juliana Hudson, Jose Luna, Nicole Wilson, Robin Petering, Darlene Woo, Milind Tambe, Eric Rice
2018 A* conf
Equilibrium Computation and Robust Optimization in Zero Sum Games With Submodular Structure.
AAAI
Bryan Wilder
2018 A* conf
Maximizing Influence in an Unknown Social Network.
AAAI
Bryan Wilder, Nicole Immorlica, Eric Rice, Milind Tambe
2018 J jnl
Melding the Data-Decisions Pipeline: Decision-Focused Learning for Combinatorial Optimization.
CoRR
Bryan Wilder, Bistra Dilkina, Milind Tambe
2018 A conf
Optimizing Network Structure for Preventative Health.
AAMAS
Bryan Wilder, Han-Ching Ou, Kayla de la Haye, Milind Tambe
2018 A* conf
Preventing Infectious Disease in Dynamic Populations Under Uncertainty.
AAAI
Bryan Wilder, Sze-Chuan Suen, Milind Tambe
2018 — conf
Preventing Infectious Disease in Dynamic Populations Under Uncertainty.
AAAI Workshops
Bryan Wilder, Sze-Chuan Suen, Milind Tambe
2018 A* conf
Risk-Sensitive Submodular Optimization.
AAAI
Bryan Wilder
2018 C conf
Utilizing Housing Resources for Homeless Youth Through the Lens of Multiple Multi-Dimensional Knapsacks.
AIES
Hau Chan, Long Tran-Thanh, Bryan Wilder, Eric Rice, Phebe Vayanos, Milind Tambe
2017 J jnl
AI in Informal Science Education: Bringing Turing Back to Life to Perform the Turing Test.
Int. J. Artif. Intell. Educ.
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
2017 J jnl
Activating the "Breakfast Club": Modeling Influence Spread in Natural-World Social Networks.
CoRR
Lily Hu, Bryan Wilder, Amulya Yadav, Eric Rice, Milind Tambe
2017 J jnl
Controlling Elections through Social Influence.
CoRR
Bryan Wilder, Yevgeniy Vorobeychik
2017 J jnl
Equilibrium computation for zero sum games with submodular structure.
CoRR
Bryan Wilder
2017 A conf
Influence Maximization in the Field: The Arduous Journey from Emerging to Deployed Application.
AAMAS
Amulya Yadav, Bryan Wilder, Eric Rice, Robin Petering, Jaih Craddock, Amanda Yoshioka-Maxwell, Mary Hemler, Laura Onasch-Vera, Milind Tambe, Darlene Woo
2017 — conf
Influence Maximization with an Unknown Network by Exploiting Community Structure.
SocInf@IJCAI
Bryan Wilder, Nicole Immorlica, Eric Rice, Milind Tambe
2017 J jnl
Remembering a Conversation - A Conversational Memory Architecture for Embodied Conversational Agents.
J. Intell. Syst.
Miguel Elvir, Avelino J. Gonzalez, Christopher Walls, Bryan Wilder
2017 A conf
Uncharted but not Uninfluenced: Influence Maximization with an Uncertain Network.
AAMAS
Bryan Wilder, Amulya Yadav, Nicole Immorlica, Eric Rice, Milind Tambe
2016 — conf
Divide to Defend: Collusive Security Games.
GameSec
Shahrzad Gholami, Bryan Wilder, Matthew Brown, Dana Thomas, Nicole D. Sintov, Milind Tambe
2016 J jnl
On the Critical Role of Divergent Selection in Evolvability.
Frontiers Robotics AI
Joel Lehman, Bryan Wilder, Kenneth O. Stanley
2016 A conf
SPECTRE: A Game Theoretic Framework for Preventing Collusion in Security Games (Demonstration).
AAMAS
Shahrzad Gholami, Bryan Wilder, Matthew Brown, Arunesh Sinha, Nicole D. Sintov, Milind Tambe
2016 A conf
Toward Addressing Collusion Among Human Adversaries in Security Games.
ECAI
Shahrzad Gholami, Bryan Wilder, Matthew Brown, Dana Thomas, Nicole D. Sintov, Milind Tambe
2015 J jnl
Reconciling explanations for the evolution of evolvability.
Adapt. Behav.
Bryan Wilder, Kenneth O. Stanley