109 citations · 228 across the 8 of their papers we have counts for
9 papers
Improved Sliding Window Algorithms for Clustering and Coverage via Bucketing-Based Sketches
Alessandro Epasto, Mohammad Mahdian, Vahab Mirrokni +1
Streaming computation plays an important role in large-scale data analysis. The sliding window model is a model of streaming computation which also captures the recency of the data…
Massively Parallel and Dynamic Algorithms for Minimum Size Clustering
Alessandro Epasto, Mohammad Mahdian, Vahab Mirrokni +1
In this paper, we study the -gather problem, a natural formulation of minimum-size clustering in metric spaces. The goal of -gather is to partition points into clusters s…
Fair Hierarchical Clustering
Sara Ahmadian, Alessandro Epasto, Marina Knittel +6
As machine learning has become more prevalent, researchers have begun to recognize the necessity of ensuring machine learning systems are fair. Recently, there has been an interest…
Sliding Window Algorithms for k-Clustering Problems
Michele Borassi, Alessandro Epasto, Silvio Lattanzi +2
The sliding window model of computation captures scenarios in which data is arriving continuously, but only the latest elements should be used for analysis. The goal is to desi…
Fair Correlation Clustering
Sara Ahmadian, Alessandro Epasto, Ravi Kumar +1
In this paper, we study correlation clustering under fairness constraints. Fair variants of -median and -center clustering have been studied recently, and approximation algor…
Fair Correlation Clustering
Saba Ahmadi, Sainyam Galhotra, Barna Saha +1
In this paper we study the problem of correlation clustering under fairness constraints. In the classic correlation clustering problem, we are given a complete graph where each edg…