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ICDM
2006
IEEE
225views Data Mining» more  ICDM 2006»
13 years 11 months ago
Adaptive Kernel Principal Component Analysis with Unsupervised Learning of Kernels
Choosing an appropriate kernel is one of the key problems in kernel-based methods. Most existing kernel selection methods require that the class labels of the training examples ar...
Daoqiang Zhang, Zhi-Hua Zhou, Songcan Chen
ICDM
2006
IEEE
193views Data Mining» more  ICDM 2006»
13 years 11 months ago
Feature Subset Selection on Multivariate Time Series with Extremely Large Spatial Features
Several spatio-temporal data collected in many applications, such as fMRI data in medical applications, can be represented as a Multivariate Time Series (MTS) matrix with m rows (...
Hyunjin Yoon, Cyrus Shahabi
CGF
2008
128views more  CGF 2008»
13 years 5 months ago
Hierarchical Convex Approximation of 3D Shapes for Fast Region Selection
Given a 3D solid model S represented by a tetrahedral mesh, we describe a novel algorithm to compute a hierarchy of convex polyhedra that tightly enclose S. The hierarchy can be b...
Marco Attene, Michela Mortara, Michela Spagnuolo, ...
WACV
2008
IEEE
13 years 11 months ago
Object Categorization Based on Kernel Principal Component Analysis of Visual Words
In recent years, many researchers are studying object categorization problem. It is reported that bag of keypoints approach which is based on local features without topological in...
Kazuhiro Hotta
DMIN
2006
124views Data Mining» more  DMIN 2006»
13 years 6 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