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CVPR
2010
IEEE
15 years 3 months ago
Large-Scale Image Categorization with Explicit Data Embedding
Kernel machines rely on an implicit mapping of the data such that non-linear classification in the original space corresponds to linear classification in the new space. As kernel ...
Florent Perronnin, Jorge Sanchez, Yan Liu
ESANN
2007
15 years 1 months ago
A novel kernel-based method for local pattern extraction in random process signals
In many applications, one is interested to detect certain patterns in random process signals. We consider a class of random process signals which contain sub similarities at rando...
Majid Beigi, Andreas Zell
ICCS
2004
Springer
15 years 5 months ago
Chunking-Coordinated-Synthetic Approaches to Large-Scale Kernel Machines
We consider a kernel-based approach to nonlinear classification that coordinates the generation of “synthetic” points (to be used in the kernel) with “chunking” (working wi...
Francisco J. González-Castaño, Rober...
ICML
2007
IEEE
16 years 21 days ago
Feature selection in a kernel space
We address the problem of feature selection in a kernel space to select the most discriminative and informative features for classification and data analysis. This is a difficult ...
Bin Cao, Dou Shen, Jian-Tao Sun, Qiang Yang, Zheng...
ICPR
2008
IEEE
16 years 1 months ago
Multiple kernel learning from sets of partially matching image features
Abstract: Kernel classifiers based on Support Vector Machines (SVM) have achieved state-ofthe-art results in several visual classification tasks, however, recent publications and d...
Guo ShengYang, Min Tan, Si-Yao Fu, Zeng-Guang Hou,...