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ICASSP
2011
IEEE
14 years 6 months ago
Distributed linear discriminant analysis
Linear discriminant analysis (LDA) is a widely used feature extraction method for classification. We introduce distributed implementations of different versions of LDA, suitable ...
Sergio Valcarcel Macua, Pavle Belanovic, Santiago ...
146
Voted
CVPR
2012
IEEE
13 years 4 months ago
Non-negative low rank and sparse graph for semi-supervised learning
Constructing a good graph to represent data structures is critical for many important machine learning tasks such as clustering and classification. This paper proposes a novel no...
Liansheng Zhuang, Haoyuan Gao, Zhouchen Lin, Yi Ma...
119
Voted
MM
2005
ACM
122views Multimedia» more  MM 2005»
15 years 7 months ago
Image clustering with tensor representation
We consider the problem of image representation and clustering. Traditionally, an n1 × n2 image is represented by a vector in the Euclidean space Rn1×n2 . Some learning algorith...
Xiaofei He, Deng Cai, Haifeng Liu, Jiawei Han
CVPR
2009
IEEE
16 years 9 months ago
The Geometry of 2D Image Signals
This paper covers a fundamental problem of local phase based signal processing: the isotropic generalization of the classical 1D analytic signal to two dimensions. The well know...
Lennart Wietzke (Kiel University), Gerald Sommer (...
ICCV
2007
IEEE
16 years 4 months ago
Graph Based Discriminative Learning for Robust and Efficient Object Tracking
Object tracking is viewed as a two-class 'one-versusrest' classification problem, in which the sample distribution of the target is approximately Gaussian while the back...
Xiaoqin Zhang, Weiming Hu, Stephen J. Maybank, Xi ...