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ICPR
2010
IEEE
13 years 5 months ago
Multiple Kernel Learning with High Order Kernels
Previous Multiple Kernel Learning approaches (MKL) employ different kernels by their linear combination. Though some improvements have been achieved over methods using single kerne...
Shuhui Wang, Shuqiang Jiang, Qingming Huang, Qi Ti...
CORR
2012
Springer
214views Education» more  CORR 2012»
12 years 3 months ago
Stochastic Low-Rank Kernel Learning for Regression
We present a novel approach to learn a kernelbased regression function. It is based on the use of conical combinations of data-based parameterized kernels and on a new stochastic ...
Pierre Machart, Thomas Peel, Liva Ralaivola, Sandr...
ICASSP
2009
IEEE
14 years 2 months ago
On combinations of CMA equalizers
We extend the affine combination of one fast and one slow least meansquare (LMS) filter to blind equalization, considering the combination of two constant modulus algorithms (CM...
Renator Candido, Magno T. M. Silva, Vitor H. Nasci...
TCOM
2010
79views more  TCOM 2010»
13 years 2 months ago
Power Correlation Coefficient of a Very General Fading Model in Maximal Ratio Combining
A very general fading scenario is considered for which exact, closed-form formulas for the correlation coefficient of the instantaneous power at the output of a Maximal Ratio Combi...
José Ricardo Mendes, Michel Daoud Yacoub, U...
ICPR
2008
IEEE
14 years 8 months ago
Combining content and structure similarity for XML document classification using composite SVM kernels
Combination of structure and content features is necessary for effective retrieval and classification of XML documents. Composite kernels provide a way for fusion of content and s...
Pabitra Mitra, Saptarshi Ghosh