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L2-norm multiple kernel learning and its application to biomedical data fusion

BMC bioinformatics, 2010-06, Vol.11 (1), p.309-309, Article 309

2010

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Support Vector Machine Classifier With Pinball Loss

IEEE transactions on pattern analysis and machine intelligence, 2014-05, Vol.36 (5), p.984-997

2014

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Concurrent monitoring of operating condition deviations and process dynamics anomalies with slow feature analysis

AIChE journal, 2015-11, Vol.61 (11), p.3666-3682

2015

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Automated structural health monitoring based on adaptive kernel spectral clustering

Mechanical systems and signal processing, 2017-06, Vol.90, p.64-78

2017

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Learning with tensors: a framework based on convex optimization and spectral regularization

Machine learning, 2014-03, Vol.94 (3), p.303-351

2014

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Multiway Spectral Clustering with Out-of-Sample Extensions through Weighted Kernel PCA

IEEE transactions on pattern analysis and machine intelligence, 2010-02, Vol.32 (2), p.335-347

2010

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Robust Low-Rank Tensor Recovery With Regularized Redescending M-Estimator

IEEE transaction on neural networks and learning systems, 2016-09, Vol.27 (9), p.1933-1946

2016

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A tutorial on support vector machine-based methods for classification problems in chemometrics

Analytica chimica acta, 2010-04, Vol.665 (2), p.129-145

2010

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Explaining Support Vector Machines: A Color Based Nomogram

PloS one, 2016-10, Vol.11 (10), p.e0164568-e0164568

2016

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Coupled Simulated Annealing

IEEE transactions on systems, man and cybernetics. Part B, Cybernetics, 2010-04, Vol.40 (2), p.320-335

2010

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Sequential minimal optimization for SVM with pinball loss

Neurocomputing (Amsterdam), 2015-02, Vol.149, p.1596-1603

2015

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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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Noise Level Estimation for Model Selection in Kernel PCA Denoising

IEEE transaction on neural networks and learning systems, 2015-11, Vol.26 (11), p.2650-2663

2015

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Learning with continuous piecewise linear decision trees

Expert systems with applications, 2021-04, Vol.168, p.114214, Article 114214

2021

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Multi-Class Supervised Novelty Detection

IEEE transactions on pattern analysis and machine intelligence, 2014-12, Vol.36 (12), p.2510-2523

2014

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A kernel-based framework to tensorial data analysis

Neural networks, 2011-10, Vol.24 (8), p.861-874

2011

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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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LS-SVM based spectral clustering and regression for predicting maintenance of industrial machines

Engineering applications of artificial intelligence, 2015-01, Vol.37, p.268-278

2015

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Multiclass Semisupervised Learning Based Upon Kernel Spectral Clustering

IEEE transaction on neural networks and learning systems, 2015-04, Vol.26 (4), p.720-733

2015

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Load forecasting using a multivariate meta-learning system

Expert systems with applications, 2013-09, Vol.40 (11), p.4427-4437

2013

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Support vector methods for survival analysis: a comparison between ranking and regression approaches

Artificial intelligence in medicine, 2011-10, Vol.53 (2), p.107-118

2011

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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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Kernelized Elastic Net Regularization: Generalization Bounds, and Sparse Recovery

Neural computation, 2016-03, Vol.28 (3), p.525-562

2016

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Efficient evolutionary spectral clustering

Pattern recognition letters, 2016-12, Vol.84, p.78-84

2016

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Benchmarking Least Squares Support Vector Machine Classifiers

Machine learning, 2004-01, Vol.54 (1), p.5-32

2004

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L2-norm multiple kernel learning and its application to biomedical data fusion

Support Vector Machine Classifier With Pinball Loss

Concurrent monitoring of operating condition deviations and process dynamics anomalies with slow feature analysis

Automated structural health monitoring based on adaptive kernel spectral clustering

Learning with tensors: a framework based on convex optimization and spectral regularization

Multiway Spectral Clustering with Out-of-Sample Extensions through Weighted Kernel PCA

Robust Low-Rank Tensor Recovery With Regularized Redescending M-Estimator

A tutorial on support vector machine-based methods for classification problems in chemometrics

Explaining Support Vector Machines: A Color Based Nomogram

Coupled Simulated Annealing

Sequential minimal optimization for SVM with pinball loss

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

Noise Level Estimation for Model Selection in Kernel PCA Denoising

Learning with continuous piecewise linear decision trees

Multi-Class Supervised Novelty Detection

A kernel-based framework to tensorial data analysis

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

LS-SVM based spectral clustering and regression for predicting maintenance of industrial machines

Multiclass Semisupervised Learning Based Upon Kernel Spectral Clustering

Load forecasting using a multivariate meta-learning system

Support vector methods for survival analysis: a comparison between ranking and regression approaches

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

Kernelized Elastic Net Regularization: Generalization Bounds, and Sparse Recovery

Efficient evolutionary spectral clustering

Benchmarking Least Squares Support Vector Machine Classifiers

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