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» Dynamically Adapting Kernels in Support Vector Machines
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CVPR
2009
IEEE
15 years 7 months ago
Classification of tensors and fiber tracts using Mercer-kernels encoding soft probabilistic spatial and diffusion information
In this paper, we present a kernel-based approach to the clustering of diffusion tensors and fiber tracts. We propose to use a Mercer kernel over the tensor space where both spati...
Radhouène Neji, Nikos Paragios, Gilles Fleu...
FLAIRS
2004
15 years 5 months ago
Gene Expression Data Classification with Revised Kernel Partial Least Squares Algorithm
One important feature of the gene expression data is that the number of genes M far exceeds the number of samples N. Standard statistical methods do not work well when N < M. D...
ZhenQiu Liu, Dechang Chen
TCS
2008
15 years 3 months ago
Kernel methods for learning languages
This paper studies a novel paradigm for learning formal languages from positive and negative examples which consists of mapping strings to an appropriate highdimensional feature s...
Leonid Kontorovich, Corinna Cortes, Mehryar Mohri
SDM
2009
SIAM
161views Data Mining» more  SDM 2009»
16 years 1 months ago
Feature Weighted SVMs Using Receiver Operating Characteristics.
Support Vector Machines (SVMs) are a leading tool in classification and pattern recognition and the kernel function is one of its most important components. This function is used...
Shaoyi Zhang, M. Maruf Hossain, Md. Rafiul Hassan,...
DAS
2010
Springer
15 years 7 months ago
A kernel-based approach to document retrieval
In this paper we tackle the problem of document image retrieval by combining a similarity measure between documents and the probability that a given document belongs to a certain ...
Albert Gordo, Jaume Gibert, Ernest Valveny, Mar&cc...