3 citations · 3 across the 3 of their papers we have counts for
5 papers · 1 filter
A Fixed Parameter Sublinear Time Approximation Scheme for Metric Min-Sum Clustering
Karthik C. S., Euiwoong Lee, Yuval Rabani +2
Metric -minsum clustering is a simple, natural, appealing density-based clustering criterion whose computational complexity remains poorly understood, despite the progress achie…
Spectral Dual Fitting for -Means
Aditya Anand, Moses Charikar, Vincent Cohen-Addad +5
We give a new dual fitting algorithm which gives improved approximation ratios of and for -Means in (high-dimensional) Euclidean and genera…
An Improved Greedy Approximation for (Metric) -Means
Moses Charikar, Vincent Cohen-Addad, Ruiquan Gao +3
Clustering is a basic task in data analysis and machine learning, and the optimization of clustering objectives are well-studied optimization problems; amongst these, the -Means…
A -Approximation Algorithm for Metric -Median
Vincent Cohen-Addad, Fabrizio Grandoni, Euiwoong Lee +2
In the classical NP-hard metric -median problem, we are given a set of clients and centers with metric distances between them, along with an integer parameter . The…
On Approximability of Min-Sum Clustering
Karthik C. S., Euiwoong Lee, Yuval Rabani +2
The min-sum -clustering problem is to partition an input set into clusters to minimize . Although $\ell_2^2…