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PAMI
2008
391views more  PAMI 2008»
13 years 9 months ago
Riemannian Manifold Learning
Recently, manifold learning has been widely exploited in pattern recognition, data analysis, and machine learning. This paper presents a novel framework, called Riemannian manifold...
Tong Lin, Hongbin Zha
GPB
2010
231views Solid Modeling» more  GPB 2010»
13 years 7 months ago
Mining Gene Expression Profiles: An Integrated Implementation of Kernel Principal Component Analysis and Singular Value Decompos
The detection of genes that show similar profiles under different experimental conditions is often an initial step in inferring the biological significance of such genes. Visualiz...
Ferran Reverter, Esteban Vegas, Pedro Sánch...
ICDE
2007
IEEE
189views Database» more  ICDE 2007»
14 years 4 months ago
Integration of Motion Capture and EMG data for Classifying the Human Motions
Three dimensional motion capture facility is a powerful tool for quantitative and qualitative assessment of multijoint external movements. Electro-myograph (EMG) signals give the ...
Gaurav N. Pradhan, Navzer D. Engineer, Mihai Nadin...
PKDD
2009
Springer
153views Data Mining» more  PKDD 2009»
14 years 4 months ago
Subspace Regularization: A New Semi-supervised Learning Method
Most existing semi-supervised learning methods are based on the smoothness assumption that data points in the same high density region should have the same label. This assumption, ...
Yan-Ming Zhang, Xinwen Hou, Shiming Xiang, Cheng-L...
NIPS
2007
13 years 11 months ago
Locality and low-dimensions in the prediction of natural experience from fMRI
Functional Magnetic Resonance Imaging (fMRI) provides dynamical access into the complex functioning of the human brain, detailing the hemodynamic activity of thousands of voxels d...
Francois Meyer, Greg Stephens