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SCIA
2005
Springer
137views Image Analysis» more  SCIA 2005»
14 years 2 months ago
Invariance in Kernel Methods by Haar-Integration Kernels
Abstract. We address the problem of incorporating transformation invariance in kernels for pattern analysis with kernel methods. We introduce a new class of kernels by so called Ha...
Bernard Haasdonk, A. Vossen, Hans Burkhardt
CAIP
1997
Springer
14 years 20 days ago
Optimally Rotation-Equivariant Directional Derivative Kernels
Abstract. We describe a framework for the design of directional derivative kernels for two-dimensional discrete signals in which we optimize a measure of rotation-equivariance in t...
Hany Farid, Eero P. Simoncelli
APSEC
2006
IEEE
14 years 2 months ago
Cohesion Analysis in Linux Kernel
It is widely accepted that strong coupling such as common coupling should be used with caution among modules. Linux kernel is analyzed in terms of these common coupling instances ...
K. Vinay Kumar Reddy, D. Janakiram
KDD
2007
ACM
197views Data Mining» more  KDD 2007»
14 years 9 months ago
Learning the kernel matrix in discriminant analysis via quadratically constrained quadratic programming
The kernel function plays a central role in kernel methods. In this paper, we consider the automated learning of the kernel matrix over a convex combination of pre-specified kerne...
Jieping Ye, Shuiwang Ji, Jianhui Chen
BICOB
2010
Springer
13 years 6 months ago
Multiple Kernel Learning for Fold Recognition
Fold recognition is a key problem in computational biology that involves classifying protein sharing structural similarities into classes commonly known as "folds". Rece...
Huzefa Rangwala