Jorge López Lázaro

Akiko Takeda

Expert Syst. Appl., 2018

2015

Linear convergence rate for the MDM algorithm for the Nearest Point Problem.

[BibT_eX]

[DOI]

Pattern Recognit., 2015

Geometric intuition and algorithms for Ev-SVM.

[BibT_eX]

[DOI]

Akiko Takeda

J. Mach. Learn. Res., 2015

2013

The convergence rate of linearly separable SMO.

[BibT_eX]

[DOI]

Proceedings of the 2013 International Joint Conference on Neural Networks, 2013

2012

Simple Proof of Convergence of the SMO Algorithm for Different SVM Variants.

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks Learn. Syst., 2012

The convergence rate of the MDM algorithm.

[BibT_eX]

[DOI]

Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN), 2012

2011

Clipping algorithms for solving the nearest point problem over reduced convex hulls.

[BibT_eX]

[DOI]

Pattern Recognit., 2011

First and Second Order SMO Algorithms for LS-SVM Classifiers.

[BibT_eX]

[DOI]

Johan A. K. Suykens

Neural Process. Lett., 2011

Convergence of algorithms for solving the Nearest Point Problem in Reduced Convex Hulls.

[BibT_eX]

[DOI]

Proceedings of the 2011 International Joint Conference on Neural Networks, 2011

Momentum Acceleration of Least-Squares Support Vector Machines.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2011, 2011

Sparse LS-SVMs with L0 - norm minimization.

[BibT_eX]

[DOI]

Proceedings of the 19th European Symposium on Artificial Neural Networks, 2011

2010

An MDM solver for the nearest point problem in Scaled Convex Hulls.

[BibT_eX]

[DOI]

Proceedings of the International Joint Conference on Neural Networks, 2010

A Common Framework for the Convergence of the GSK, MDM and SMO Algorithms.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks, 2010

Least 1-Norm SVMs: a new SVM variant between standard and LS-SVMs.

[BibT_eX]

[DOI]

Proceedings of the 18th European Symposium on Artificial Neural Networks, 2010

2009

Finding optimal model parameters by deterministic and annealed focused grid search.

[BibT_eX]

[DOI]

Neurocomputing, 2009

Cycle-breaking acceleration of SVM training.

[BibT_eX]

[DOI]

Neurocomputing, 2009

A Simple Proof of the Convergence of the SMO Algorithm for Linearly Separable Problems.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks, 2009

Rosen's projection method for SVM training.

[BibT_eX]

[DOI]

Proceedings of the 17th European Symposium on Artificial Neural Networks, 2009

2008

Finding Optimal Model Parameters by Discrete Grid Search.

[BibT_eX]

[DOI]

Proceedings of the Innovations in Hybrid Intelligent Systems, 2008

On the Equivalence of the SMO and MDM Algorithms for SVM Training.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2008

A 4-Vector MDM Algorithm for Support Vector Training.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks, 2008

Simple Clipping Algorithms for Reduced Convex Hull SVM Training.

[BibT_eX]

[DOI]

Proceedings of the Hybrid Artificial Intelligence Systems, Third International Workshop, 2008

An accelerated MDM algorithm for SVM training.

[BibT_eX]

[DOI]

Proceedings of the 16th European Symposium on Artificial Neural Networks, 2008

2007

Square Penalty Support Vector Regression.

[BibT_eX]

[DOI]