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» Learning subspace kernels for classification
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NPL
2006
130views more  NPL 2006»
13 years 7 months ago
A Fast Feature-based Dimension Reduction Algorithm for Kernel Classifiers
This paper presents a novel dimension reduction algorithm for kernel based classification. In the feature space, the proposed algorithm maximizes the ratio of the squared between-c...
Senjian An, Wanquan Liu, Svetha Venkatesh, Ronny T...
ICPR
2008
IEEE
14 years 8 months ago
Fast protein homology and fold detection with sparse spatial sample kernels
In this work we present a new string similarity feature, the sparse spatial sample (SSS). An SSS is a set of short substrings at specific spatial displacements contained in the or...
Pai-Hsi Huang, Pavel P. Kuksa, Vladimir Pavlovic
BMVC
2010
13 years 5 months ago
Histogram of Body Poses and Spectral Regression Discriminant Analysis for Human Action Categorization
This paper explores a recently proposed and rarely reported subspace learning method, Spectral Regression Discriminant Analysis (SRDA) [1, 2], on silhouette based human action rec...
Ling Shao, Xiuli Chen
ICML
2002
IEEE
14 years 8 months ago
Syllables and other String Kernel Extensions
During the last years, the use of string kernels that compare documents has been shown to achieve good results on text classification problems. In this paper we introduce the appl...
Craig Saunders, Hauke Tschach, John Shawe-Taylor
ACCV
2010
Springer
13 years 2 months ago
Randomised Manifold Forests for Principal Angle-Based Face Recognition
Abstract. In set-based face recognition, each set of face images is often represented as a linear/nonlinear manifold and the Principal Angles (PA) or Kernel PAs are exploited to me...
Ujwal D. Bonde, Tae-Kyun Kim, K. R. Ramakrishnan