76 search results - page 4 / 16 » Optimal In-Place Learning and the Lobe Component Analysis |
ECCV
2002
Springer
14 years 8 months ago
2002
Springer
Principal ComponentAnalysis (PCA) has been successfully applied to construct linear models of shape, graylevel, and motion. In particular, PCA has been widely used to model the var...
JMLR
2010
13 years 1 months ago
2010
Principal component analysis (PCA) is a classical data analysis technique that finds linear transformations of data that retain the maximal amount of variance. We study a case whe...
NIPS
2003
13 years 7 months ago
2003
Principal components analysis (PCA) is one of the most widely used techniques in machine learning and data mining. Minor components analysis (MCA) is less well known, but can also...
AI
2005
Springer
13 years 6 months ago
2005
Springer
Abstract. The protein family classification problem, which consists of determining the family memberships of given unknown protein sequences, is very important for a biologist for ...
JMLR
2010
13 years 1 months ago
2010
We present an extension of sparse PCA, or sparse dictionary learning, where the sparsity patterns of all dictionary elements are structured and constrained to belong to a prespeci...