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TEC
2008
149views more  TEC 2008»
15 years 6 months ago
Biogeography-Based Optimization
Abstract--We propose a novel variation to biogeographybased optimization (BBO), which is an evolutionary algorithm (EA) developed for global optimization. The new algorithm employs...
Dan Simon
TSP
2010
15 years 1 months ago
Learning graphical models for hypothesis testing and classification
Sparse graphical models have proven to be a flexible class of multivariate probability models for approximating high-dimensional distributions. In this paper, we propose techniques...
Vincent Y. F. Tan, Sujay Sanghavi, John W. Fisher ...
CORR
2007
Springer
167views Education» more  CORR 2007»
15 years 6 months ago
Optimal Solutions for Sparse Principal Component Analysis
Given a sample covariance matrix, we examine the problem of maximizing the variance explained by a linear combination of the input variables while constraining the number of nonze...
Alexandre d'Aspremont, Francis R. Bach, Laurent El...
NCA
2007
IEEE
15 years 6 months ago
Ensemble of hybrid neural network learning approaches for designing pharmaceutical drugs
Designing drugs is a current problem in the pharmaceutical research. By designing a drug we mean to choose some variables of drug formulation (inputs), for obtaining optimal charac...
Ajith Abraham, Crina Grosan, Stefan Tigan
JMLR
2006
124views more  JMLR 2006»
15 years 6 months ago
A Direct Method for Building Sparse Kernel Learning Algorithms
Many kernel learning algorithms, including support vector machines, result in a kernel machine, such as a kernel classifier, whose key component is a weight vector in a feature sp...
Mingrui Wu, Bernhard Schölkopf, Gökhan H...