Search Results for author: Bryan Wilder

Found 17 papers, 6 papers with code

Learning (Local) Surrogate Loss Functions for Predict-Then-Optimize Problems

no code implementations30 Mar 2022 Sanket Shah, Bryan Wilder, Andrew Perrault, Milind Tambe

Decision-Focused Learning (DFL) is a paradigm for tailoring a predictive model to a downstream optimisation task that uses its predictions, so that it can perform better on that specific task.

End-to-End Constrained Optimization Learning: A Survey

no code implementations30 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.

Tracking disease outbreaks from sparse data with Bayesian inference

no code implementations12 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.

Bayesian Inference Epidemiology +1

Automatically Learning Compact Quality-aware Surrogates for Optimization Problems

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.

Portfolio Optimization

Fuzzy c-Means Clustering for Persistence Diagrams

1 code implementation4 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.

Model Selection Topological Data Analysis

Learning to Complement Humans

no code implementations1 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.

Medical Diagnosis

MIPaaL: Mixed Integer Program as a Layer

no code implementations12 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.

Decision Making

Influence maximization in unknown social networks: Learning Policies for Effective Graph Sampling

1 code implementation8 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.

Graph Sampling

End to end learning and optimization on graphs

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.

Link Prediction

SATNet: Bridging deep learning and logical reasoning using a differentiable satisfiability solver

3 code implementations29 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.

Game of Suduko

Group-Fairness in Influence Maximization

1 code implementation3 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

End-to-End Game-Focused Learning of Adversary Behavior in Security Games

no code implementations3 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.

Learning to Prescribe Interventions for Tuberculosis Patients Using Digital Adherence Data

no code implementations5 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.

Melding the Data-Decisions Pipeline: Decision-Focused Learning for Combinatorial Optimization

no code implementations14 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.

Combinatorial Optimization

Algorithmic Social Intervention

no code implementations14 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.

Decision Making Decision Making Under Uncertainty

Distributionally Robust Submodular Maximization

no code implementations14 Feb 2018 Matthew Staib, Bryan Wilder, Stefanie Jegelka

We also show compelling empirical evidence that DRO improves generalization to the unknown stochastic submodular function.

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