Vincent Cohen-Addad

activity

20202026

most citedImproved Approximations for Euclidean

k

-means and

k

-median, via Nested Quasi-Independent Sets

6 citations · 26 across the 22 of their papers we have counts for

collaborators

Showing 2022Show all

3 papers · 1 filter

cs.DS2022★ 2 cited

Scalable Differentially Private Clustering via Hierarchically Separated Trees

Vincent Cohen-Addad, Alessandro Epasto, Silvio Lattanzi +5

We study the private $k$ -median and $k$ -means clustering problem in $d$ dimensional Euclidean space. By leveraging tree embeddings, we give an efficient and easy to implement algor…

cs.DS2022★ 6 cited

Improved Approximations for Euclidean $k$ -means and $k$ -median, via Nested Quasi-Independent Sets

Vincent Cohen-Addad, Hossein Esfandiari, Vahab Mirrokni +1

Motivated by data analysis and machine learning applications, we consider the popular high-dimensional Euclidean $k$ -median and $k$ -means problems. We propose a new primal-dual alg…

cs.LG2022★ 3 cited

Near-Optimal Correlation Clustering with Privacy

Vincent Cohen-Addad, Chenglin Fan, Silvio Lattanzi +4

Correlation clustering is a central problem in unsupervised learning, with applications spanning community detection, duplicate detection, automated labelling and many more. In the…

Scalable Differentially Private Clustering via Hierarchically Separated Trees

Improved Approximations for Euclidean k-means and k-median, via Nested Quasi-Independent Sets

Near-Optimal Correlation Clustering with Privacy

Improved Approximations for Euclidean $k$ -means and $k$ -median, via Nested Quasi-Independent Sets