34 citations · 68 across the 17 of their papers we have counts for
4 papers · 1 filter
Improved Approximation Algorithms for Stochastic-Matching Problems
Marek Adamczyk, Brian Brubach, Fabrizio Grandoni +3
We consider the Stochastic Matching problem, which is motivated by applications in kidney exchange and online dating. In this problem, we are given an undirected graph. Each edge i…
Stochastic Optimization and Learning for Two-Stage Supplier Problems
Brian Brubach, Nathaniel Grammel, David G. Harris +3
The main focus of this paper is radius-based (supplier) clustering in the two-stage stochastic setting with recourse, where the inherent stochasticity of the model comes in the for…
A Pairwise Fair and Community-preserving Approach to k-Center Clustering
Brian Brubach, Darshan Chakrabarti, John P. Dickerson +3
Clustering is a foundational problem in machine learning with numerous applications. As machine learning increases in ubiquity as a backend for automated systems, concerns about fa…
Probabilistic Fair Clustering
Seyed A. Esmaeili, Brian Brubach, Leonidas Tsepenekas +1
In clustering problems, a central decision-maker is given a complete metric graph over vertices and must provide a clustering of vertices that minimizes some objective function. In…