no code implementations • 14 Feb 2018 • Matthew Staib, Bryan Wilder, Stefanie Jegelka
We also show compelling empirical evidence that DRO improves generalization to the unknown stochastic submodular function.
no code implementations • 14 Mar 2018 • Bryan Wilder
Social and behavioral interventions are a critical tool for governments and communities to tackle deep-rooted societal challenges such as homelessness, disease, and poverty.
no code implementations • 14 Sep 2018 • Bryan Wilder, Bistra Dilkina, Milind Tambe
These components are typically approached separately: a machine learning model is first trained via a measure of predictive accuracy, and then its predictions are used as input into an optimization algorithm which produces a decision.
no code implementations • 5 Feb 2019 • Jackson A. Killian, Bryan Wilder, Amit Sharma, Daksha Shah, Vinod Choudhary, Bistra Dilkina, Milind Tambe
Digital Adherence Technologies (DATs) are an increasingly popular method for verifying patient adherence to many medications.
no code implementations • 3 Mar 2019 • Andrew Perrault, Bryan Wilder, Eric Ewing, Aditya Mate, Bistra Dilkina, Milind Tambe
Stackelberg security games are a critical tool for maximizing the utility of limited defense resources to protect important targets from an intelligent adversary.
1 code implementation • 3 Mar 2019 • Alan Tsang, Bryan Wilder, Eric Rice, Milind Tambe, Yair Zick
Influence maximization is a widely used model for information dissemination in social networks.
Computer Science and Game Theory Social and Information Networks
3 code implementations • 29 May 2019 • Po-Wei Wang, Priya L. Donti, Bryan Wilder, Zico Kolter
We demonstrate that by integrating this solver into end-to-end learning systems, we can learn the logical structure of challenging problems in a minimally supervised fashion.
Ranked #1 on Game of Sudoku on Sudoku 9x9
1 code implementation • NeurIPS 2019 • Bryan Wilder, Eric Ewing, Bistra Dilkina, Milind Tambe
However, graphs or related attributes are often only partially observed, introducing learning problems such as link prediction which must be solved prior to optimization.
1 code implementation • 8 Jul 2019 • Harshavardhan Kamarthi, Priyesh Vijayan, Bryan Wilder, Balaraman Ravindran, Milind Tambe
A serious challenge when finding influential actors in real-world social networks is the lack of knowledge about the structure of the underlying network.
no code implementations • 12 Jul 2019 • Aaron Ferber, Bryan Wilder, Bistra Dilkina, Milind Tambe
It has been successfully applied to several limited combinatorial problem classes, such as those that can be expressed as linear programs (LP), and submodular optimization.
no code implementations • 1 May 2020 • Bryan Wilder, Eric Horvitz, Ece Kamar
A rising vision for AI in the open world centers on the development of systems that can complement humans for perceptual, diagnostic, and reasoning tasks.
1 code implementation • 4 Jun 2020 • Thomas Davies, Jack Aspinall, Bryan Wilder, Long Tran-Thanh
We end with experiments on two datasets that utilise both the topological and fuzzy nature of our algorithm: pre-trained model selection in machine learning and lattices structures from materials science.
2 code implementations • NeurIPS 2020 • Kai Wang, Bryan Wilder, Andrew Perrault, Milind Tambe
Solving optimization problems with unknown parameters often requires learning a predictive model to predict the values of the unknown parameters and then solving the problem using these values.
no code implementations • 12 Sep 2020 • Bryan Wilder, Michael J. Mina, Milind Tambe
For example, case counts may be sparse when only a small fraction of infections are caught by a testing program.
no code implementations • 30 Mar 2021 • James Kotary, Ferdinando Fioretto, Pascal Van Hentenryck, Bryan Wilder
This paper surveys the recent attempts at leveraging machine learning to solve constrained optimization problems.
no code implementations • 7 Jul 2021 • Kai Wang, Bryan Wilder, Sze-chuan Suen, Bistra Dilkina, Milind Tambe
We introduce a novel decomposed GP regression to incorporate the subgroup decomposed feedback.
no code implementations • 30 Mar 2022 • Sanket Shah, Kai Wang, Bryan Wilder, Andrew Perrault, Milind Tambe
Decision-Focused Learning (DFL) is a paradigm for tailoring a predictive model to a downstream optimization task that uses its predictions in order to perform better on that specific task.
no code implementations • 6 Feb 2023 • Aditya Mate, Bryan Wilder, Aparna Taneja, Milind Tambe
We consider the task of evaluating policies of algorithmic resource allocation through randomized controlled trials (RCTs).
no code implementations • 29 Mar 2023 • Michael Poli, Stefano Massaroli, Stefano Ermon, Bryan Wilder, Eric Horvitz
We present a methodology for formulating simplifying abstractions in machine learning systems by identifying and harnessing the utility structure of decisions.
no code implementations • 26 May 2023 • Sanket Shah, Andrew Perrault, Bryan Wilder, Milind Tambe
In this paper, we propose solutions to these issues, avoiding the aforementioned assumptions and utilizing the ML model's features to increase the sample efficiency of learning loss functions.
1 code implementation • NeurIPS 2023 • Ben Chugg, Santiago Cortes-Gomez, Bryan Wilder, Aaditya Ramdas
Whereas previous work relies on a fixed-sample size, our methods are sequential and allow for the continuous monitoring of incoming data, making them highly amenable to tracking the fairness of real-world systems.
2 code implementations • 29 Jun 2023 • Ananya Joshi, Kathryn Mazaitis, Roni Rosenfeld, Bryan Wilder
However, existing outlier detection frameworks perform poorly on this task because they do not account for the data volume or for the statistical properties of public health streams.
no code implementations • 5 Jul 2023 • Ruiqi Lyu, Bryan Wilder, Roni Rosenfeld
The surveillance of a pandemic is a challenging task, especially when crucial data is distributed and stakeholders cannot or are unwilling to share.
no code implementations • 2 Jan 2024 • Ananya Joshi, Tina Townes, Nolan Gormley, Luke Neureiter, Roni Rosenfeld, Bryan Wilder
Disease control experts inspect public health data streams daily for outliers worth investigating, like those corresponding to data quality issues or disease outbreaks.
no code implementations • 18 Mar 2024 • Yewon Byun, Dylan Sam, Michael Oberst, Zachary C. Lipton, Bryan Wilder
A fundamental problem in decision-making systems is the presence of inequity across demographic lines.