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» Learning of Boolean Functions Using Support Vector Machines
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CSE
2009
IEEE
14 years 2 months ago
Predicting Interests of People on Online Social Networks
—We introduce a new data set which contains both a self-declared friendship network and self-chosen attributes from a finite list defined by the social networking site. We prop...
Apoorv Agarwal, Owen Rambow, Nandini Bhardwaj
BICOB
2009
Springer
13 years 11 months ago
Constrained Fisher Scores Derived from Interaction Profile Hidden Markov Models Improve Protein to Protein Interaction Predictio
Protein-protein interaction plays critical roles in cellular functions. In this work, we propose a computational method to predict protein-protein interaction by using support vec...
Alvaro J. González, Li Liao
ESANN
2007
13 years 9 months ago
Optimizing kernel parameters by second-order methods
Radial basis function network (RBF) kernels are widely used for support vector machines (SVMs). But for model selection of an SVM, we need to optimize the kernel parameter and the ...
Shigeo Abe
ICCV
2005
IEEE
14 years 1 months ago
Image Based Regression Using Boosting Method
We present a general algorithm of image based regression that is applicable to many vision problems. The proposed regressor that targets a multiple-output setting is learned using...
Shaohua Kevin Zhou, Bogdan Georgescu, Xiang Sean Z...
BMCBI
2008
101views more  BMCBI 2008»
13 years 7 months ago
Term-tissue specific models for prediction of gene ontology biological processes using transcriptional profiles of aging in dros
Background: Predictive classification on the base of gene expression profiles appeared recently as an attractive strategy for identifying the biological functions of genes. Gene O...
Wensheng Zhang, Sige Zou, Jiuzhou Song