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NN
1998
Springer
177views Neural Networks» more  NN 1998»
14 years 9 months ago
Soft vector quantization and the EM algorithm
The relation between hard c-means (HCM), fuzzy c-means (FCM), fuzzy learning vector quantization (FLVQ), soft competition scheme (SCS) of Yair et al. (1992) and probabilistic Gaus...
Ethem Alpaydin
BMCBI
2006
119views more  BMCBI 2006»
14 years 9 months ago
LS-NMF: A modified non-negative matrix factorization algorithm utilizing uncertainty estimates
Background: Non-negative matrix factorisation (NMF), a machine learning algorithm, has been applied to the analysis of microarray data. A key feature of NMF is the ability to iden...
Guoli Wang, Andrew V. Kossenkov, Michael F. Ochs
NIPS
1997
14 years 10 months ago
EM Algorithms for PCA and SPCA
I present an expectation-maximization (EM) algorithm for principal component analysis (PCA). The algorithm allows a few eigenvectors and eigenvalues to be extracted from large col...
Sam T. Roweis
KDD
2010
ACM
242views Data Mining» more  KDD 2010»
14 years 11 months ago
A scalable two-stage approach for a class of dimensionality reduction techniques
Dimensionality reduction plays an important role in many data mining applications involving high-dimensional data. Many existing dimensionality reduction techniques can be formula...
Liang Sun, Betul Ceran, Jieping Ye
COCO
2006
Springer
96views Algorithms» more  COCO 2006»
15 years 1 months ago
Optimal Hardness Results for Maximizing Agreements with Monomials
We consider the problem of finding a monomial (or a term) that maximizes the agreement rate with a given set of examples over the Boolean hypercube. The problem is motivated by le...
Vitaly Feldman