37 search results - page 3 / 8 » Covariance Estimation for High Dimensional Data Vectors Usin... |
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...
KDD
2001
ACM
14 years 8 months ago
2001
ACM
Random projections have recently emerged as a powerful method for dimensionality reduction. Theoretical results indicate that the method preserves distances quite nicely; however,...
ICML
2008
IEEE
14 years 8 months ago
2008
IEEE
We study the problem of finding the dominant eigenvector of the sample covariance matrix, under additional constraints on the vector: a cardinality constraint limits the number of...
CORR
2007
Springer
13 years 7 months ago
2007
Springer
This paper derives a near optimal distributed Kalman filter to estimate a large-scale random field monitored by a network of N sensors. The field is described by a sparsely con...
SDM
2011
SIAM
12 years 10 months ago
2011
SIAM
Latent semantic analysis (LSA), as one of the most popular unsupervised dimension reduction tools, has a wide range of applications in text mining and information retrieval. The k...