14 search results - page 2 / 3 » Unsupervised discovery of co-occurrence in sparse high dimen... |
ICCV
2011
IEEE
12 years 7 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...
ICIP
2010
IEEE
13 years 5 months ago
2010
IEEE
Face recognition (FR) is an active yet challenging topic in computer vision applications. As a powerful tool to represent high dimensional data, recently sparse representation bas...
SADM
2010
13 years 2 months ago
2010
This paper is concerned with classifying high dimensional data into one of two categories. In various settings, such as when dealing with fMRI and microarray data, the number of v...
ICPP
2000
IEEE
13 years 11 months ago
2000
IEEE
Clustering is a data mining problem which finds dense regions in a sparse multi-dimensional data set. The attribute values and ranges of these regions characterize the clusters. ...
BMCBI
2007
2007
Penalized likelihood for sparse contingency tables with an application to full-length cDNA libraries
13 years 7 months ago
Background: The joint analysis of several categorical variables is a common task in many areas of biology, and is becoming central to systems biology investigations whose goal is ...