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07/10/2023
SHAP@k:Efficient and Probably Approximately Correct (PAC) Identification of Top-k Features
The SHAP framework provides a principled method to explain the predictio...
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08/26/2022
Comparing Apples to Oranges: Learning Similarity Functions for Data Produced by Different Distributions
Similarity functions measure how comparable pairs of elements are, and p...
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02/16/2022
Controlling Epidemic Spread using Probabilistic Diffusion Models on Networks
The spread of an epidemic is often modeled by an SIR random process on a...
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02/09/2022
Deploying Vaccine Distribution Sites for Improved Accessibility and Equity to Support Pandemic Response
In response to COVID-19, many countries have mandated social distancing ...
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06/09/2021
Fair Disaster Containment via Graph-Cut Problems
Graph cut problems form a fundamental problem type in combinatorial opti...
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06/09/2021
A New Notion of Individually Fair Clustering: α-Equitable k-Center
Clustering is a fundamental problem in unsupervised machine learning, an...
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03/02/2021
Fairness, Semi-Supervised Learning, and More: A General Framework for Clustering with Stochastic Pairwise Constraints
Metric clustering is fundamental in areas ranging from Combinatorial Opt...
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08/07/2020
Approximation Algorithms for Radius-Based, Two-Stage Stochastic Clustering Problems with Budget Constraints
The main focus of this paper is radius-based clustering problems in the ...
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07/14/2020
A Pairwise Fair and Community-preserving Approach to k-Center Clustering
Clustering is a foundational problem in machine learning with numerous a...
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06/19/2020