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Optimal control by least squares support vector machines

Neural networks, 2001, Vol.14 (1), p.23-35

2001

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Efficiently updating and tracking the dominant kernel principal components

Neural networks, 2007-03, Vol.20 (2), p.220-229

2007

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Improved performance on high-dimensional survival data by application of Survival-SVM

Bioinformatics, 2011-01, Vol.27 (1), p.87-94

2011

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Interior-Point Lagrangian Decomposition Method for Separable Convex Optimization

Journal of optimization theory and applications, 2009-12, Vol.143 (3), p.567-588

2009

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Bayesian Framework for Least-Squares Support Vector Machine Classifiers, Gaussian Processes, and Kernel Fisher Discriminant Analysis

Neural computation, 2002-05, Vol.14 (5), p.1115-1147

2002

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Application of Kernel Principal Component Analysis for Single-Lead-ECG-Derived Respiration

IEEE transactions on biomedical engineering, 2012-04, Vol.59 (4), p.1169-1176

2012

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Additive regularization trade-off : Fusion of training and validation levels in kernel methods

Machine learning, 2006-03, Vol.62 (3), p.217-252

2006

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Reducing the Number of Support Vectors of SVM Classifiers Using the Smoothed Separable Case Approximation

IEEE transaction on neural networks and learning systems, 2012-04, Vol.23 (4), p.682-688

2012

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Optimized fixed-size kernel models for large data sets

Computational statistics & data analysis, 2010-06, Vol.54 (6), p.1484-1504

2010

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Sequentially activated groups in neural networks

Europhysics letters, 2009-06, Vol.86 (6), p.60006-60006P6

2009

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Preoperative diagnosis of ovarian tumors using Bayesian kernel‐based methods

Ultrasound in obstetrics & gynecology, 2007-05, Vol.29 (5), p.496-504

2007

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Influence of passive elements on the dynamics of oscillatory ensembles of cardiac cells

Physical review. E, Statistical, nonlinear, and soft matter physics, 2009-04, Vol.79 (4 Pt 2), p.046219-046219, Article 046219

2009

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Metastable states and transient activity in ensembles of excitatory and inhibitory elements

Europhysics letters, 2010-07, Vol.91 (2), p.20006

2010

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A Convex Approach to Validation-Based Learning of the Regularization Constant

IEEE transaction on neural networks and learning systems, 2007-05, Vol.18 (3), p.917-920

2007

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Confidence bands for least squares support vector machine classifiers: A regression approach

Pattern recognition, 2012-06, Vol.45 (6), p.2280-2287

2012

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Additive survival least-squares support vector machines

Statistics in medicine, 2010-01, Vol.29 (2), p.296-308

2010

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Support vector machines versus logistic regression: improving prospective performance in clinical decision‐making

Ultrasound in obstetrics & gynecology, 2006-06, Vol.27 (6), p.607-608

2006

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A Comparison of Pruning Algorithms for Sparse Least Squares Support Vector Machines

Lecture notes in computer science, 2004, p.1247-1253

2004

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Optimized Data Fusion for Kernel k-Means Clustering

IEEE transactions on pattern analysis and machine intelligence, 2012-05, Vol.34 (5), p.1031-1039

2012

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Knowledge discovery in a direct marketing case using least squares support vector machines

International journal of intelligent systems, 2001-09, Vol.16 (9), p.1023-1036

2001

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Approximate Solutions to Ordinary Differential Equations Using Least Squares Support Vector Machines

IEEE transaction on neural networks and learning systems, 2012-09, Vol.23 (9), p.1356-1367

2012

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Numerical studies of slow rhythms emergence in neural microcircuits: Bifurcations and stability

Chaos (Woodbury, N.Y.), 2009-03, Vol.19 (1), p.015107-015107-8

2009

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Variety of synchronous regimes in neuronal ensembles

Chaos (Woodbury, N.Y.), 2008-09, Vol.18 (3), p.037121-037121-18

2008

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Deformed Laplacians and spectral ranking in directed networks

Applied and computational harmonic analysis, 2019-09, Vol.47 (2), p.397-422

2019

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True random bit generation from a double-scroll attractor

IEEE transactions on circuits and systems. 1, Fundamental theory and applications, 2004-07, Vol.51 (7), p.1395-1404

2004

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Optimal control by least squares support vector machines

Efficiently updating and tracking the dominant kernel principal components

Improved performance on high-dimensional survival data by application of Survival-SVM

Interior-Point Lagrangian Decomposition Method for Separable Convex Optimization

Bayesian Framework for Least-Squares Support Vector Machine Classifiers, Gaussian Processes, and Kernel Fisher Discriminant Analysis

Application of Kernel Principal Component Analysis for Single-Lead-ECG-Derived Respiration

Additive regularization trade-off : Fusion of training and validation levels in kernel methods

Reducing the Number of Support Vectors of SVM Classifiers Using the Smoothed Separable Case Approximation

Optimized fixed-size kernel models for large data sets

Sequentially activated groups in neural networks

Preoperative diagnosis of ovarian tumors using Bayesian kernel‐based methods

Influence of passive elements on the dynamics of oscillatory ensembles of cardiac cells

Metastable states and transient activity in ensembles of excitatory and inhibitory elements

A Convex Approach to Validation-Based Learning of the Regularization Constant

Confidence bands for least squares support vector machine classifiers: A regression approach

Additive survival least-squares support vector machines

Support vector machines versus logistic regression: improving prospective performance in clinical decision‐making

A Comparison of Pruning Algorithms for Sparse Least Squares Support Vector Machines

Optimized Data Fusion for Kernel k-Means Clustering

Knowledge discovery in a direct marketing case using least squares support vector machines

Approximate Solutions to Ordinary Differential Equations Using Least Squares Support Vector Machines

Numerical studies of slow rhythms emergence in neural microcircuits: Bifurcations and stability

Variety of synchronous regimes in neuronal ensembles

Deformed Laplacians and spectral ranking in directed networks

True random bit generation from a double-scroll attractor

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