59 search results - page 6 / 12 » Sparse Higher-Order Principal Components Analysis |
SDM
2010
SIAM
13 years 7 months ago
2010
SIAM
A popular approach for dimensionality reduction and data analysis is principal component analysis (PCA). A limiting factor with PCA is that it does not inform us on which of the o...
JMLR
2012
11 years 11 months ago
2012
We study sparse principal components analysis in the high-dimensional setting, where p (the number of variables) can be much larger than n (the number of observations). We prove o...
ICML
2007
IEEE
14 years 9 months ago
2007
IEEE
Eigenvalue problems are rampant in machine learning and statistics and appear in the context of classification, dimensionality reduction, etc. In this paper, we consider a cardina...
CNSR
2011
IEEE
13 years 3 days ago
2011
IEEE
—Network delay is a crucial metric for evaluating the state of the network. We present in this paper a structural analysis of network delay, based on delay measurements of a back...
ECCV
2008
Springer
13 years 9 months ago
2008
Springer
—This paper presents a fast part-based subspace selection algorithm, termed the binary sparse nonnegative matrix factorization (B-SNMF). Both the training process and the testing...