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» Classification via semi-Riemannian spaces
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CVPR
2008
IEEE
8 years 9 months ago
Classification via semi-Riemannian spaces
In this paper, we develop a geometric framework for linear or nonlinear discriminant subspace learning and classification. In our framework, the structures of classes are conceptu...
Deli Zhao, Zhouchen Lin, Xiaoou Tang
TKDE
2011
479views more  TKDE 2011»
8 years 2 months ago
Learning Semi-Riemannian Metrics for Semisupervised Feature Extraction
—Discriminant feature extraction plays a central role in pattern recognition and classification. Linear Discriminant Analysis (LDA) is a traditional algorithm for supervised feat...
Wei Zhang, Zhouchen Lin, Xiaoou Tang
QI
2009
Springer
190views Physics» more  QI 2009»
9 years 1 months ago
Characterizing Pure High-Order Entanglements in Lexical Semantic Spaces via Information Geometry
An emerging topic in Quantuam Interaction is the use of lexical semantic spaces, as Hilbert spaces, to capture the meaning of words. There has been some initial evidence that the p...
Yuexian Hou, Dawei Song
SSPR
2004
Springer
9 years 22 days ago
Optimizing Classification Ensembles via a Genetic Algorithm for a Web-Based Educational System
Classification fusion combines multiple classifications of data into a single classification solution of greater accuracy. Feature extraction aims to reduce the computational cost ...
Behrouz Minaei-Bidgoli, Gerd Kortemeyer, William F...
CVPR
2007
IEEE
9 years 9 months ago
Human Detection via Classification on Riemannian Manifolds
We present a new algorithm to detect humans in still images utilizing covariance matrices as object descriptors. Since these descriptors do not lie on a vector space, well known m...
Oncel Tuzel, Fatih Porikli, Peter Meer
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