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CIBCB
2005
IEEE
14 years 1 months ago
Feature Selection for Microarray Data Using Least Squares SVM and Particle Swarm Optimization
Feature selection is an important preprocessing technique for many pattern recognition problems. When the number of features is very large while the number of samples is relatively...
E. Ke Tang, Ponnuthurai N. Suganthan, Xin Yao
BMCBI
2010
97views more  BMCBI 2010»
13 years 7 months ago
Kinome-wide interaction modelling using alignment-based and alignment-independent approaches for kinase description and linear a
Background: Protein kinases play crucial roles in cell growth, differentiation, and apoptosis. Abnormal function of protein kinases can lead to many serious diseases, such as canc...
Maris Lapinsh, Jarl E. S. Wikberg
MICRO
2005
IEEE
130views Hardware» more  MICRO 2005»
14 years 1 months ago
Exploiting Vector Parallelism in Software Pipelined Loops
An emerging trend in processor design is the addition of short vector instructions to general-purpose and embedded ISAs. Frequently, these extensions are employed using traditiona...
Samuel Larsen, Rodric M. Rabbah, Saman P. Amarasin...
FLAIRS
2004
13 years 9 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
BMCBI
2010
182views more  BMCBI 2010»
13 years 7 months ago
L2-norm multiple kernel learning and its application to biomedical data fusion
Background: This paper introduces the notion of optimizing different norms in the dual problem of support vector machines with multiple kernels. The selection of norms yields diff...
Shi Yu, Tillmann Falck, Anneleen Daemen, Lé...