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ICASSP
2011
IEEE
14 years 3 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 ...
CVPR
2012
IEEE
13 years 2 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...
MM
2005
ACM
122views Multimedia» more  MM 2005»
15 years 5 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 7 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 1 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 ...