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» Clustering with Bregman Divergences
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KDD
2012
ACM
212views Data Mining» more  KDD 2012»
11 years 10 months ago
Fast bregman divergence NMF using taylor expansion and coordinate descent
Non-negative matrix factorization (NMF) provides a lower rank approximation of a matrix. Due to nonnegativity imposed on the factors, it gives a latent structure that is often mor...
Liangda Li, Guy Lebanon, Haesun Park
TIT
2010
158views Education» more  TIT 2010»
13 years 2 months ago
Belief propagation, Dykstra's algorithm, and iterated information projections
Belief propagation is shown to be an instance of a hybrid between two projection algorithms in the convex programming literature: Dykstra's algorithm with cyclic Bregman proje...
John MacLaren Walsh, Phillip A. Regalia
PAMI
2006
128views more  PAMI 2006»
13 years 7 months ago
On Weighting Clustering
Recent papers and patents in iterative unsupervised learning have emphasized a new trend in clustering. It basically consists of penalizing solutions via weights on the instance po...
Richard Nock, Frank Nielsen
PKDD
2009
Springer
138views Data Mining» more  PKDD 2009»
14 years 2 days ago
Cost-Sensitive Learning Based on Bregman Divergences
Raúl Santos-Rodríguez, Alicia Guerre...
ALT
2009
Springer
14 years 4 months ago
Approximation Algorithms for Tensor Clustering
Abstract. We present the first (to our knowledge) approximation algorithm for tensor clustering—a powerful generalization to basic 1D clustering. Tensors are increasingly common...
Stefanie Jegelka, Suvrit Sra, Arindam Banerjee