A simple approach to sparse clustering

Author:

Arias-Castro Ery,Pu Xiao

Publisher

Elsevier BV

Subject

Applied Mathematics,Computational Theory and Mathematics,Computational Mathematics,Statistics and Probability

Reference28 articles.

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2. k-means++: The advantages of careful seeding;Arthur,2007

3. Azizyan, M., Singh, A., Wasserman, L., 2013. Minimax theory for high-dimensional Gaussian mixtures with sparse mean separation, in: Neural Information Processing Systems (NIPS).

4. Hill-climbing finds random planted bisections;Carson,2001

5. Using evidence of mixed populations to select variables for clustering very high-dimensional data;Chan;J. Amer. Statist. Assoc.,2010

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