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ORCIDBryan Wilder
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2020 – today
- 2024
[c51]Sanket Shah, Bryan Wilder, Andrew Perrault, Milind Tambe:
Leaving the Nest: Going beyond Local Loss Functions for Predict-Then-Optimize. AAAI 2024: 14902-14909- [c50]Ananya Joshi, Tina Townes, Nolan Gormley, Luke Neureiter, Roni Rosenfeld
, Bryan Wilder:
Outlier Ranking for Large-Scale Public Health Data. AAAI 2024: 22176-22184 - [c49]Yewon Byun, Dylan Sam, Michael Oberst, Zachary C. Lipton, Bryan Wilder:
Auditing Fairness under Unobserved Confounding. AISTATS 2024: 4339-4347 - [c48]Santiago Cortes-Gomez, Mateo Dulce Rubio, Carlos Miguel Patiño, Bryan Wilder:
Statistical Inference Under Constrained Selection Bias. ICML 2024 - [i41]Ananya Joshi, Tina Townes, Nolan Gormley, Luke Neureiter, Roni Rosenfeld, Bryan Wilder:
Outlier Ranking in Large-Scale Public Health Streams. CoRR abs/2401.01459 (2024) - [i40]Yewon Byun, Dylan Sam, Michael Oberst, Zachary C. Lipton, Bryan Wilder:
Auditing Fairness under Unobserved Confounding. CoRR abs/2403.14713 (2024) - [i39]Justin Whitehouse, Christopher Jung, Vasilis Syrgkanis, Bryan Wilder, Zhiwei Steven Wu:
Orthogonal Causal Calibration. CoRR abs/2406.01933 (2024) - [i38]Kevin Ren, Yewon Byun, Bryan Wilder:
Decision-Focused Evaluation of Worst-Case Distribution Shift. CoRR abs/2407.03557 (2024) - [i37]Bryan Wilder, Pim Welle:
Learning treatment effects while treating those in need. CoRR abs/2407.07596 (2024) - [i36]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 abs/2407.11973 (2024) - [i35]Santiago Cortes-Gomez, Carlos Miguel Patiño, Yewon Byun, Steven Wu, Eric Horvitz, Bryan Wilder:
Decision-Focused Uncertainty Quantification. CoRR abs/2410.01767 (2024) - [i34]Santiago Cortes-Gomez, Naveen Raman, Aarti Singh, Bryan Wilder:
Data-driven Design of Randomized Control Trials with Guaranteed Treatment Effects. CoRR abs/2410.11212 (2024) - [i33]Khurram Yamin, Vibhhu Sharma, Ed Kennedy, Bryan Wilder:
Accounting for Missing Covariates in Heterogeneous Treatment Estimation. CoRR abs/2410.15655 (2024) - [i32]Khurram Yamin, Shantanu Gupta, Gaurav R. Ghosal, Zachary C. Lipton, Bryan Wilder:
Failure Modes of LLMs for Causal Reasoning on Narratives. CoRR abs/2410.23884 (2024) - 2023
- [j6]Elena Falcettoni, Dina Machuve, Bryan Wilder, Angela Zhou:
Report on the 2nd ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO 2022). SIGecom Exch. 21(1): 14-19 (2023) - [c47]Bryan Wilder:
AI for Equitable, Data-Driven Decisions in Public Health. AAAI 2023: 15459 - [c46]Michael Poli, Stefano Massaroli, Stefano Ermon, Bryan Wilder, Eric Horvitz:
Ideal Abstractions for Decision-Focused Learning. AISTATS 2023: 10223-10234 - [c45]Haipeng Chen, Bryan Wilder, Wei Qiu, Bo An, Eric Rice, Milind Tambe:
A Learning Approach to Complex Contagion Influence Maximization. AAMAS 2023: 2622-2624 - [c44]Aditya Mate, Bryan Wilder, Aparna Taneja, Milind Tambe:
Improved Policy Evaluation for Randomized Trials of Algorithmic Resource Allocation. ICML 2023: 24198-24213 - [c43]Haipeng Chen, Bryan Wilder, Wei Qiu, Bo An, Eric Rice, Milind Tambe:
Complex Contagion Influence Maximization: A Reinforcement Learning Approach. IJCAI 2023: 5531-5540 - [c42]Ananya Joshi, Kathryn Mazaitis, Roni Rosenfeld, Bryan Wilder:
Computationally Assisted Quality Control for Public Health Data Streams. IJCAI 2023: 6004-6012 - [c41]Ben Chugg, Santiago Cortes-Gomez, Bryan Wilder, Aaditya Ramdas:
Auditing Fairness by Betting. NeurIPS 2023 - [i31]Aditya Mate, Bryan Wilder, Aparna Taneja, Milind Tambe:
Improved Policy Evaluation for Randomized Trials of Algorithmic Resource Allocation. CoRR abs/2302.02570 (2023) - [i30]Michael Poli, Stefano Massaroli, Stefano Ermon, Bryan Wilder, Eric Horvitz:
Ideal Abstractions for Decision-Focused Learning. CoRR abs/2303.17062 (2023) - [i29]Sanket Shah, Andrew Perrault, Bryan Wilder, Milind Tambe:
Leaving the Nest: Going Beyond Local Loss Functions for Predict-Then-Optimize. CoRR abs/2305.16830 (2023) - [i28]Ben Chugg, Santiago Cortes-Gomez, Bryan Wilder, Aaditya Ramdas:
Auditing Fairness by Betting. CoRR abs/2305.17570 (2023) - [i27]Santiago Cortes-Gomez, Mateo Dulce Rubio, Bryan Wilder:
Inference under constrained distribution shifts. CoRR abs/2306.03302 (2023) - [i26]Ananya Joshi, Kathryn Mazaitis, Roni Rosenfeld, Bryan Wilder:
Computationally Assisted Quality Control for Public Health Data Streams. CoRR abs/2306.16914 (2023) - [i25]Ruiqi Lyu, Bryan Wilder, Roni Rosenfeld:
Federated Epidemic Surveillance. CoRR abs/2307.02616 (2023) - 2022
- [c40]Thomas Davies, Jack Aspinall, Bryan Wilder, Tran-Thanh Long:
Fuzzy c-means clustering in persistence diagram space for deep learning model selection. NeurReps 2022: 137-157 - [c39]Sanket Shah, Kai Wang, Bryan Wilder, Andrew Perrault, Milind Tambe:
Decision-Focused Learning without Decision-Making: Learning Locally Optimized Decision Losses. NeurIPS 2022 - [i24]Sanket Shah, Bryan Wilder, Andrew Perrault, Milind Tambe:
Learning (Local) Surrogate Loss Functions for Predict-Then-Optimize Problems. CoRR abs/2203.16067 (2022) - 2021
- [j5]Bryan Wilder, Sze-Chuan Suen, Milind Tambe:
Allocating outreach resources for disease control in a dynamic population with information spread. IISE Trans. 53(6): 629-642 (2021) - [c38]Bryan Wilder, Michael J. Mina, Milind Tambe:
Tracking Disease Outbreaks from Sparse Data with Bayesian Inference. AAAI 2021: 4883-4891 - [c37]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. AAAI 2021: 14948-14956 - [c36]James Kotary, Ferdinando Fioretto, Pascal Van Hentenryck, Bryan Wilder:
End-to-End Constrained Optimization Learning: A Survey. IJCAI 2021: 4475-4482 - [i23]James Kotary, Ferdinando Fioretto, Pascal Van Hentenryck, Bryan Wilder:
End-to-End Constrained Optimization Learning: A Survey. CoRR abs/2103.16378 (2021) - [i22]Kai Wang, Bryan Wilder, Sze-Chuan Suen, Bistra Dilkina, Milind Tambe:
Harnessing Heterogeneity: Learning from Decomposed Feedback in Bayesian Modeling. CoRR abs/2107.03003 (2021) - 2020
- [c35]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: 1378-1386 - [c34]Aaron M. Ferber, Bryan Wilder, Bistra Dilkina, Milind Tambe:
MIPaaL: Mixed Integer Program as a Layer. AAAI 2020: 1504-1511 - [c33]Harshavardhan Kamarthi, Priyesh Vijayan, Bryan Wilder, Balaraman Ravindran, Milind Tambe:
Influence Maximization in Unknown Social Networks: Learning Policies for Effective Graph Sampling. AAMAS 2020: 575-583 - [c32]Bryan Wilder, Eric Horvitz, Ece Kamar:
Learning to Complement Humans. IJCAI 2020: 1526-1533 - [c31]Kai Wang, Bryan Wilder, Andrew Perrault, Milind Tambe:
Automatically Learning Compact Quality-aware Surrogates for Optimization Problems. NeurIPS 2020 - [i21]Bryan Wilder, Eric Horvitz, Ece Kamar:
Learning to Complement Humans. CoRR abs/2005.00582 (2020) - [i20]Thomas O. M. Davies, Jack Aspinall, Bryan Wilder, Long Tran-Thanh:
Fuzzy c-Means Clustering for Persistence Diagrams. CoRR abs/2006.02796 (2020) - [i19]Aida Rahmattalabi, Phebe Vayanos, Anthony Fulginiti, Eric Rice, Bryan Wilder, Amulya Yadav, Milind Tambe:
Exploring Algorithmic Fairness in Robust Graph Covering Problems. CoRR abs/2006.06865 (2020) - [i18]Kai Wang, Bryan Wilder, Andrew Perrault, Milind Tambe:
Automatically Learning Compact Quality-aware Surrogates for Optimization Problems. CoRR abs/2006.10815 (2020) - [i17]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 abs/2007.07747 (2020) - [i16]Bryan Wilder, Michael J. Mina, Milind Tambe:
Tracking disease outbreaks from sparse data with Bayesian inference. CoRR abs/2009.05863 (2020) - [i15]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 abs/2009.09559 (2020)
2010 – 2019
- 2019
- [c30]Bryan Wilder, Bistra Dilkina, Milind Tambe:
Melding the Data-Decisions Pipeline: Decision-Focused Learning for Combinatorial Optimization. AAAI 2019: 1658-1665 - [c29]Bryan Wilder, Yevgeniy Vorobeychik:
Defending Elections against Malicious Spread of Misinformation. AAAI 2019: 2213-2220 - [c28]Matthew Staib, Bryan Wilder, Stefanie Jegelka:
Distributionally Robust Submodular Maximization. AISTATS 2019: 506-516 - [c27]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: 6545-6554 - [c26]Alan Tsang, Bryan Wilder, Eric Rice, Milind Tambe, Yair Zick:
Group-Fairness in Influence Maximization. IJCAI 2019: 5997-6005 - [c25]Bryan Wilder:
AI at the Margins: Data, Decisions, and Inclusive Social Impact. IJCAI 2019: 6474-6475 - [c24]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: 2430-2438 - [c23]Bryan Wilder, Eric Ewing, Bistra Dilkina, Milind Tambe:
End to end learning and optimization on graphs. NeurIPS 2019: 4674-4685 - [c22]Aida Rahmattalabi, Phebe Vayanos, Anthony Fulginiti, Eric Rice, Bryan Wilder, Amulya Yadav, Milind Tambe:
Exploring Algorithmic Fairness in Robust Graph Covering Problems. NeurIPS 2019: 15750-15761 - [c21]Kai Wang, Bryan Wilder, Sze-Chuan Suen, Bistra Dilkina, Milind Tambe:
Improving GP-UCB Algorithm by Harnessing Decomposed Feedback. PKDD/ECML Workshops (1) 2019: 555-569 - [i14]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 abs/1902.01506 (2019) - [i13]Andrew Perrault, Bryan Wilder, Eric Ewing, Aditya Mate, Bistra Dilkina, Milind Tambe:
Decision-Focused Learning of Adversary Behavior in Security Games. CoRR abs/1903.00958 (2019) - [i12]Alan Tsang, Bryan Wilder, Eric Rice, Milind Tambe, Yair Zick:
Group-Fairness in Influence Maximization. CoRR abs/1903.00967 (2019) - [i11]Po-Wei Wang, Priya L. Donti, Bryan Wilder, J. Zico Kolter:
SATNet: Bridging deep learning and logical reasoning using a differentiable satisfiability solver. CoRR abs/1905.12149 (2019) - [i10]Bryan Wilder, Eric Ewing, Bistra Dilkina, Milind Tambe:
End to end learning and optimization on graphs. CoRR abs/1905.13732 (2019) - [i9]Aaron M. Ferber, Bryan Wilder, Bistra Dilkina, Milind Tambe:
MIPaaL: Mixed Integer Program as a Layer. CoRR abs/1907.05912 (2019) - [i8]Harshavardhan Kamarthi, Priyesh Vijayan, Bryan Wilder, Balaraman Ravindran, Milind Tambe:
Learning policies for Social network discovery with Reinforcement learning. CoRR abs/1907.11625 (2019) - 2018
- [c20]Bryan Wilder, Sze-Chuan Suen, Milind Tambe:
Preventing Infectious Disease in Dynamic Populations Under Uncertainty. AAAI Workshops 2018: 522-529 - [c19]Bryan Wilder, Sze-Chuan Suen, Milind Tambe:
Preventing Infectious Disease in Dynamic Populations Under Uncertainty. AAAI 2018: 841-848 - [c18]Bryan Wilder:
Equilibrium Computation and Robust Optimization in Zero Sum Games With Submodular Structure. AAAI 2018: 1274-1281 - [c17]Bryan Wilder, Nicole Immorlica, Eric Rice, Milind Tambe:
Maximizing Influence in an Unknown Social Network. AAAI 2018: 4743-4750 - [c16]Bryan Wilder:
Risk-Sensitive Submodular Optimization. AAAI 2018: 6451-6458 - [c15]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: 41-47 - [c14]Bryan Wilder, Yevgeniy Vorobeychik:
Controlling Elections through Social Influence. AAMAS 2018: 265-273 - [c13]Bryan Wilder, Han-Ching Ou, Kayla de la Haye, Milind Tambe:
Optimizing Network Structure for Preventative Health. AAMAS 2018: 841-849 - [c12]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: 1414-1422 - [c11]Lily Hu, Bryan Wilder, Amulya Yadav, Eric Rice, Milind Tambe:
Activating the: Modeling Influence Spread in Natural-World Social Networks. AAMAS 2018: 1631-1639 - [c10]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: 35-51 - [c9]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: 181-192 - [c8]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: 5399-5403 - [c7]Bryan Wilder:
Algorithmic Social Intervention. IJCAI 2018: 5793-5794 - [i7]Matthew Staib, Bryan Wilder, Stefanie Jegelka:
Distributionally Robust Submodular Maximization. CoRR abs/1802.05249 (2018) - [i6]Bryan Wilder:
Algorithmic Social Intervention. CoRR abs/1803.05098 (2018) - [i5]Bryan Wilder, Bistra Dilkina, Milind Tambe:
Melding the Data-Decisions Pipeline: Decision-Focused Learning for Combinatorial Optimization. CoRR abs/1809.05504 (2018) - [i4]Bryan Wilder, Yevgeniy Vorobeychik:
Defending Elections Against Malicious Spread of Misinformation. CoRR abs/1809.05521 (2018) - 2017
- [j4]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): 353-384 (2017) - [j3]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): 1-21 (2017) - [c6]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: 150-158 - [c5]Bryan Wilder, Amulya Yadav, Nicole Immorlica, Eric Rice, Milind Tambe:
Uncharted but not Uninfluenced: Influence Maximization with an Uncertain Network. AAMAS 2017: 1305-1313 - [c4]Bryan Wilder, Nicole Immorlica, Eric Rice, Milind Tambe:
Influence Maximization with an Unknown Network by Exploiting Community Structure. SocInf@IJCAI 2017: 2-7 - [i3]Lily Hu, Bryan Wilder, Amulya Yadav, Eric Rice, Milind Tambe:
Activating the "Breakfast Club": Modeling Influence Spread in Natural-World Social Networks. CoRR abs/1710.00364 (2017) - [i2]Bryan Wilder:
Equilibrium computation for zero sum games with submodular structure. CoRR abs/1710.00996 (2017) - [i1]Bryan Wilder, Yevgeniy Vorobeychik:
Controlling Elections through Social Influence. CoRR abs/1711.08615 (2017) - 2016
- [j2]Joel Lehman, Bryan Wilder, Kenneth O. Stanley:
On the Critical Role of Divergent Selection in Evolvability. Frontiers Robotics AI 3: 45 (2016) - [c3]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: 1498-1500 - [c2]Shahrzad Gholami, Bryan Wilder, Matthew Brown, Dana Thomas, Nicole D. Sintov, Milind Tambe:
Toward Addressing Collusion Among Human Adversaries in Security Games. ECAI 2016: 1750-1751 - [c1]Shahrzad Gholami, Bryan Wilder, Matthew Brown, Dana Thomas, Nicole D. Sintov, Milind Tambe:
Divide to Defend: Collusive Security Games. GameSec 2016: 272-293 - 2015
- [j1]Bryan Wilder, Kenneth O. Stanley:
Reconciling explanations for the evolution of evolvability. Adapt. Behav. 23(3): 171-179 (2015)
Coauthor Index
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