no code implementations • ICML 2020 • Brian Brubach, Darshan Chakrabarti, John P. Dickerson, Samir Khuller, Aravind Srinivasan, Leonidas Tsepenekas
Clustering is a foundational problem in machine learning with numerous applications.
1 code implementation • 2 Mar 2021 • Brian Brubach, Darshan Chakrabarti, John P. Dickerson, Aravind Srinivasan, Leonidas Tsepenekas
Metric clustering is fundamental in areas ranging from Combinatorial Optimization and Data Mining, to Machine Learning and Operations Research.
1 code implementation • 9 Jun 2021 • Darshan Chakrabarti, John P. Dickerson, Seyed A. Esmaeili, Aravind Srinivasan, Leonidas Tsepenekas
Clustering is a fundamental problem in unsupervised machine learning, and fair variants of it have recently received significant attention due to its societal implications.
no code implementations • 2 Mar 2022 • Seyed A. Esmaeili, Darshan Chakrabarti, Hayley Grape, Brian Brubach
Specifically, we define a central map which may be considered as being "most typical" and give a rigorous justification for it by showing that it mirrors the Kemeny ranking in a scenario where we have a committee voting over a collection of redistricting maps to be drawn.