Search Results for author:
Found 2 papers, 0 papers with code
Hierarchical Clustering: New Bounds and Objective
Later Cohen-Addad et al. [2019] considered the same objective function as Dasgupta's but for dissimilarity-based metrics, called $Rev(T)$.
Local Search Yields a PTAS for k-Means in Doubling Metrics
The most well known and ubiquitous clustering problem encountered in nearly every branch of science is undoubtedly $k$-means: given a set of data points and a parameter $k$, select $k$ centres and partition the data points into $k$ clusters around these centres so that the sum of squares of distances of the points to their cluster centre is minimized.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
