77 search results - page 8 / 16 » On the Anonymization of Sparse High-Dimensional Data |
ICCV
2011
IEEE
12 years 6 months ago
2011
IEEE
Linear subspace learning (LSL) is a popular approach to image recognition and it aims to reveal the essential features of high dimensional data, e.g., facial images, in a lower di...
TSP
2008
13 years 6 months ago
2008
The rapid developing area of compressed sensing suggests that a sparse vector lying in a high dimensional space can be accurately and efficiently recovered from only a small set of...
CSDA
2007
13 years 6 months ago
2007
The Lasso is an attractive regularisation method for high dimensional regression. It combines variable selection with an efficient computational procedure. However, the rate of co...
SDM
2011
SIAM
12 years 9 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...
KDD
2001
ACM
14 years 7 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,...