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MM
2004
ACM
248views Multimedia» more  MM 2004»
14 years 1 months ago
Incremental semi-supervised subspace learning for image retrieval
Subspace learning techniques are widespread in pattern recognition research. They include Principal Component Analysis (PCA), Locality Preserving Projection (LPP), etc. These tech...
Xiaofei He
BMCBI
2005
201views more  BMCBI 2005»
13 years 7 months ago
Principal component analysis for predicting transcription-factor binding motifs from array-derived data
Background: The responses to interleukin 1 (IL-1) in human chondrocytes constitute a complex regulatory mechanism, where multiple transcription factors interact combinatorially to...
Yunlong Liu, Matthew P. Vincenti, Hiroki Yokota
CVPR
2003
IEEE
14 years 9 months ago
Generalized Principal Component Analysis (GPCA)
This paper presents an algebro-geometric solution to the problem of segmenting an unknown number of subspaces of unknown and varying dimensions from sample data points. We represen...
René Vidal, Shankar Sastry, Yi Ma
DMIN
2006
124views Data Mining» more  DMIN 2006»
13 years 9 months ago
Optimal Multi-class Classification with Principal Components
An approach to build a multi-class classifier is proposed in this paper. This approach consists of a derivation to show under which loss function an optimal classifier can be obtai...
Albert Hoang
ICPR
2002
IEEE
14 years 8 months ago
Feature Selection for Pose Invariant Face Recognition
One of the major difficulties in face recognition systems is the in-depth pose variation problem. Most face recognition approaches assume that the pose of the face is known. In th...
Berk Gökberk, Ethem Alpaydin, Lale Akarun