502 search results - page 7 / 101 » Principal Component Analysis for Sparse High-Dimensional Dat... |
CIKM
2010
Springer
13 years 6 months ago
2010
Springer
Low-dimensional topic models have been proven very useful for modeling a large corpus of documents that share a relatively small number of topics. Dimensionality reduction tools s...
NIPS
1997
13 years 8 months ago
1997
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...
IJCV
2008
13 years 7 months ago
2008
For software and more illustrations: http://www.psi.utoronto.ca/anitha/fastTCA.htm Dimensionality reduction techniques such as principal component analysis and factor analysis are...
CIKM
2008
Springer
13 years 9 months ago
2008
Springer
Finding latent patterns in high dimensional data is an important research problem with numerous applications. The most well known approaches for high dimensional data analysis are...
AI
2005
Springer
13 years 7 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 ...