Interior path following primal-dual algorithms. Part II: Convex quadratic programming
Mathematical Programming: Series A and B
The nature of statistical learning theory
The nature of statistical learning theory
Multiple Cuts in the Analytic Center Cutting Plane Method
SIAM Journal on Optimization
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Machine Learning
A Feature Selection Newton Method for Support Vector Machine Classification
Computational Optimization and Applications
Feature selection algorithms to find strong genes
Pattern Recognition Letters
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The two-case pattern recognition problem aims to find the best way of linearly separate two different classes of data points with a good generalization performance.In the context of learning machines proposed to solve the pattern recognition problem, the analytic center machine (ACM) uses the analytic center cutting plane method restricted to spherical shells.In this work we prove existence and uniqueness of the analytic center of a spherical surface, which guarantees the well definedness of ACM problem. We also propose and analyze new primal, dual and primal-dual formulations based on interior point methods for the analytic center machine. Further, we provide a complexity bound on the number of iterations for the primal approach.