# Johan A. K. Suykens

According to our database1, Johan A. K. Suykens authored at least 353 papers between 1994 and 2020.

Collaborative distances:

## IEEE Fellow

IEEE Fellow 2015, "For developing the least squares support vector machines".

Book
In proceedings
Article
PhD thesis
Other

## Bibliography

2020
Transductive LSTM for time-series prediction: An application to weather forecasting.
Neural Networks, 2020

A Statistical Learning Approach to Modal Regression.
J. Mach. Learn. Res., 2020

Outlier detection in non-elliptical data by kernel MRCD.
CoRR, 2020

A Theoretical Framework for Target Propagation.
CoRR, 2020

Ensemble Kernel Methods, Implicit Regularization and Determinental Point Processes.
CoRR, 2020

The Bures Metric for Taming Mode Collapse in Generative Adversarial Networks.
CoRR, 2020

Disentangled Representation Learning and Generation with Manifold Optimization.
CoRR, 2020

Analysis of Least Squares Regularized Regression in Reproducing Kernel Krein Spaces.
CoRR, 2020

Generalizing Random Fourier Features via Generalized Measures.
CoRR, 2020

Random Features for Kernel Approximation: A Survey in Algorithms, Theory, and Beyond.
CoRR, 2020

Diversity sampling is an implicit regularization for kernel methods.
CoRR, 2020

Wasserstein Exponential Kernels.
CoRR, 2020

Robust Generative Restricted Kernel Machines using Weighted Conjugate Feature Duality.
CoRR, 2020

Efficient hinging hyperplanes neural network and its application in nonlinear system identification.
Autom., 2020

Random Fourier Features via Fast Surrogate Leverage Weighted Sampling.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Indefinite Kernel Logistic Regression With Concave-Inexact-Convex Procedure.
IEEE Trans. Neural Networks Learn. Syst., 2019

Sparse Kernel Regression with Coefficient-based $\ell_q-$regularization.
J. Mach. Learn. Res., 2019

Impulse response constrained LS-SVM modelling for MIMO Hammerstein system identification.
Int. J. Control, 2019

Robust classification of graph-based data.
Data Min. Knowl. Discov., 2019

Generative Restricted Kernel Machines.
CoRR, 2019

Nyström landmark sampling and regularized Christoffel functions.
CoRR, 2019

Two-stage Best-scored Random Forest for Large-scale Regression.
CoRR, 2019

Deep convolutional learning for general early design stage prediction models.

Axiomatic Kernels on Graphs for Support Vector Machines.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019 - 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17-19, 2019, Proceedings, 2019

Latent Space Exploration Using Generative Kernel PCA.
Proceedings of the 31st Benelux Conference on Artificial Intelligence (BNAIC 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019), 2019

Towards Deterministic Diverse Subset Sampling.
Proceedings of the 31st Benelux Conference on Artificial Intelligence (BNAIC 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019), 2019

2018
Regularized Semipaired Kernel CCA for Domain Adaptation.
IEEE Trans. Neural Networks Learn. Syst., 2018

Classification With Truncated $\ell _{1}$ Distance Kernel.
IEEE Trans. Neural Networks Learn. Syst., 2018

Parallelized Tensor Train Learning of Polynomial Classifiers.
IEEE Trans. Neural Networks Learn. Syst., 2018

Convex Formulation for Kernel PCA and Its Use in Semisupervised Learning.
IEEE Trans. Neural Networks Learn. Syst., 2018

Optimal Quadrature-Sparsification for Integral Operator Approximation.
SIAM J. Sci. Comput., 2018

Indefinite kernel spectral learning.
Pattern Recognit., 2018

Kernel Density Estimation for Dynamical Systems.
J. Mach. Learn. Res., 2018

Multi-View Kernel Spectral Clustering.
Inf. Fusion, 2018

Deep hybrid neural-kernel networks using random Fourier features.
Neurocomputing, 2018

Pinball loss minimization for one-bit compressive sensing: Convex models and algorithms.
Neurocomputing, 2018

Multi-View Least Squares Support Vector Machines Classification.
Neurocomputing, 2018

Modified Frank-Wolfe algorithm for enhanced sparsity in support vector machine classifiers.
Neurocomputing, 2018

Hammerstein system identification through best linear approximation inversion and regularisation.
Int. J. Control, 2018

Correntropy Based Matrix Completion.
Entropy, 2018

Transductive Feature Selection Using Clustering-Based Sample Entropy for Temperature Prediction in Weather Forecasting.
Entropy, 2018

Spatio-temporal Stacked LSTM for Temperature Prediction in Weather Forecasting.
CoRR, 2018

Generalization Properties of hyper-RKHS and its Application to Out-of-Sample Extensions.
CoRR, 2018

A two-experiment approach to Wiener system identification.
Autom., 2018

Deep-learning neural-network architectures and methods: Using component-based models in building-design energy prediction.

Weighted Multi-view Deep Neural Networks for Weather Forecasting.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2018, 2018

Tensor Learning in Multi-view Kernel PCA.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2018, 2018

Generative Kernel PCA.
Proceedings of the 26th European Symposium on Artificial Neural Networks, 2018

Shallow and Deep Models for Domain Adaptation problems.
Proceedings of the 26th European Symposium on Artificial Neural Networks, 2018

Proceedings of the 57th IEEE Conference on Decision and Control, 2018

Valuing Knowledge, Information and Agency in Multi-agent Reinforcement Learning: A Case Study in Smart Buildings.
Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, 2018

Solving lp-norm regularization with tensor kernels.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Solution Path for Pin-SVM Classifiers With Positive and Negative τ Values.
IEEE Trans. Neural Networks Learn. Syst., 2017

Editorial: A Successful Year and Looking Forward to 2017 and Beyond.
IEEE Trans. Neural Networks Learn. Syst., 2017

Deep Restricted Kernel Machines Using Conjugate Feature Duality.
Neural Computation, 2017

Supervised aggregated feature learning for multiple instance classification.
Inf. Sci., 2017

Fast kernel spectral clustering.
Neurocomputing, 2017

Positive semi-definite embedding for dimensionality reduction and out-of-sample extensions.
CoRR, 2017

Unpaired multi-view kernel spectral clustering.
Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

MIMO hammerstein system identification using LS-SVM and steady state time response.
Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

Multi-view LS-SVM regression for black-box temperature prediction in weather forecasting.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Probabilistic matrix factorization from quantized measurements.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

A primal-dual line search method and applications in image processing.
Proceedings of the 25th European Signal Processing Conference, 2017

Scalable Hybrid Deep Neural Kernel Networks.
Proceedings of the 25th European Symposium on Artificial Neural Networks, 2017

Moving Least Squares Support Vector Machines for weather temperature prediction.
Proceedings of the 25th European Symposium on Artificial Neural Networks, 2017

On the identification of Wiener systems with polynomial nonlinearity.
Proceedings of the 56th IEEE Annual Conference on Decision and Control, 2017

2016
Robust Low-Rank Tensor Recovery With Regularized Redescending M-Estimator.
IEEE Trans. Neural Networks Learn. Syst., 2016

IEEE Trans. Neural Networks Learn. Syst., 2016

Rank-1 Tensor Properties with Applications to a Class of Tensor Optimization Problems.
SIAM J. Optim., 2016

Efficient evolutionary spectral clustering.
Pattern Recognit. Lett., 2016

Coordinate Descent Algorithm for Ramp Loss Linear Programming Support Vector Machines.
Neural Process. Lett., 2016

Learning Theory Estimates with Observations from General Stationary Stochastic Processes.
Neural Computation, 2016

Robust Support Vector Machines for Classification with Nonconvex and Smooth Losses.
Neural Computation, 2016

Kernelized Elastic Net Regularization: Generalization Bounds, and Sparse Recovery.
Neural Computation, 2016

Fast and scalable Lasso via stochastic Frank-Wolfe methods with a convergence guarantee.
Mach. Learn., 2016

Reweighted stochastic learning.
Neurocomputing, 2016

Entropy-Based Incomplete Cholesky Decomposition for a Scalable Spectral Clustering Algorithm: Computational Studies and Sensitivity Analysis.
Entropy, 2016

Estimating the unknown time delay in chemical processes.
Eng. Appl. Artif. Intell., 2016

Magnetic Eigenmaps for Visualization of Directed Networks.
CoRR, 2016

Magnetic eigenmaps for community detection in directed networks.
CoRR, 2016

Convex Formulation for Kernel PCA and its Use in Semi-Supervised Learning.
CoRR, 2016

The effect of imposing 'fractional abundance constraints' onto the multilayer perceptron for sub-pixel land cover classification.
Int. J. Appl. Earth Obs. Geoinformation, 2016

Scalable Semi-supervised kernel spectral learning using random Fourier features.
Proceedings of the 2016 IEEE Symposium Series on Computational Intelligence, 2016

Multi-label semi-supervised learning using regularized kernel spectral clustering.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

Denoised Kernel Spectral data Clustering.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

Clustering-based feature selection for black-box weather temperature prediction.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

Hammerstein system identification using LS-SVM and steady state time response.
Proceedings of the 2016 European Control Conference, 2016

Fast in-memory spectral clustering using a fixed-size approach.
Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

Spatio-temporal feature selection for black-box weather forecasting.
Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

Clustering from two data sources using a kernel-based approach with weight coupling.
Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

Efficient Sparse Approximation of Support Vector Machines Solving a Kernel Lasso.
Proceedings of the Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2016

Efficient multiple scale kernel classifiers.
Proceedings of the 2016 IEEE International Conference on Big Data, 2016

2015
Kernel Methods.
Proceedings of the Springer Handbook of Computational Intelligence, 2015

Noise Level Estimation for Model Selection in Kernel PCA Denoising.
IEEE Trans. Neural Networks Learn. Syst., 2015

Multiclass Semisupervised Learning Based Upon Kernel Spectral Clustering.
IEEE Trans. Neural Networks Learn. Syst., 2015

Very Sparse LSSVM Reductions for Large-Scale Data.
IEEE Trans. Neural Networks Learn. Syst., 2015

A Rank-One Tensor Updating Algorithm for Tensor Completion.
IEEE Signal Process. Lett., 2015

Signal recovery for jointly sparse vectors with different sensing matrices.
Signal Process., 2015

Two-level ℓ<sub>1</sub> minimization for compressed sensing.
Signal Process., 2015

Identifying intervals for hierarchical clustering using the Gershgorin circle theorem.
Pattern Recognit. Lett., 2015

Incremental multi-class semi-supervised clustering regularized by Kalman filtering.
Neural Networks, 2015

Learning with the maximum correntropy criterion induced losses for regression.
J. Mach. Learn. Res., 2015

Learning solutions to partial differential equations using LS-SVM.
Neurocomputing, 2015

Sequential minimal optimization for SVM with pinball loss.
Neurocomputing, 2015

A robust ensemble approach to learn from positive and unlabeled data using SVM base models.
Neurocomputing, 2015

LS-SVM based spectral clustering and regression for predicting maintenance of industrial machines.
Eng. Appl. Artif. Intell., 2015

Higher order Matching Pursuit for Low Rank Tensor Learning.
CoRR, 2015

Kernel Spectral Clustering and applications.
CoRR, 2015

Pinball Loss Minimization for One-bit Compressive Sensing.
CoRR, 2015

Fixed-Size Least Squares Support Vector Machines: Scala Implementation for Large Scale Classification.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2015

Hierarchical semi-supervised clustering using KSC based model.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

Kernel spectral document clustering using unsupervised precision-recall metrics.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

Black-box modeling for temperature prediction in weather forecasting.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

A PARTAN-accelerated Frank-Wolfe algorithm for large-scale SVM classification.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

Ranking Overlap and Outlier Points in Data using Soft Kernel Spectral Clustering.
Proceedings of the 23rd European Symposium on Artificial Neural Networks, 2015

Incorporating Best Linear Approximation within LS-SVM-based Hammerstein System Identification.
Proceedings of the 54th IEEE Conference on Decision and Control, 2015

Regularized and sparse stochastic k-means for distributed large-scale clustering.
Proceedings of the 2015 IEEE International Conference on Big Data, 2015

KSC-net: Community Detection for Big Data Networks.
Proceedings of the Big Data - Algorithms, Analytics, and Applications., 2015

2014
Improved Initialization for Nonlinear State-Space Modeling.
IEEE Trans. Instrum. Meas., 2014

Hybrid Coupled Local Minimizers.
IEEE Trans. Circuits Syst. I Regul. Pap., 2014

Multi-Class Supervised Novelty Detection.
IEEE Trans. Pattern Anal. Mach. Intell., 2014

Support Vector Machine Classifier With Pinball Loss.
IEEE Trans. Pattern Anal. Mach. Intell., 2014

Learning with tensors: a framework based on convex optimization and spectral regularization.
Mach. Learn., 2014

Ramp loss linear programming support vector machine.
J. Mach. Learn. Res., 2014

EnsembleSVM: a library for ensemble learning using support vector machines.
J. Mach. Learn. Res., 2014

QoS prediction for web service compositions using kernel-based quantile estimation with online adaptation of the constant offset.
Inf. Sci., 2014

Non-parallel support vector classifiers with different loss functions.
Neurocomputing, 2014

Incremental kernel spectral clustering for online learning of non-stationary data.
Neurocomputing, 2014

Asymmetric least squares support vector machine classifiers.
Comput. Stat. Data Anal., 2014

Asymmetric v-tube support vector regression.
Comput. Stat. Data Anal., 2014

Multilevel Hierarchical Kernel Spectral Clustering for Real-Life Large Scale Complex Networks.
CoRR, 2014

Complexity Issues and Randomization Strategies in Frank-Wolfe Algorithms for Machine Learning.
CoRR, 2014

Fast Prediction with SVM Models Containing RBF Kernels.
CoRR, 2014

Hybrid Conditional Gradient - Smoothing Algorithms with Applications to Sparse and Low Rank Regularization.
CoRR, 2014

Parameter estimation of delay differential equations: An integration-free LS-SVM approach.
Commun. Nonlinear Sci. Numer. Simul., 2014

Predicting breast cancer using an expression values weighted clinical classifier.
BMC Bioinform., 2014

Quantile regression with ℓ 1 - regularization and Gaussian kernels.

Reweighted l 2-Regularized Dual Averaging Approach for Highly Sparse Stochastic Learning.
Proceedings of the Advances in Neural Networks - ISNN 2014, 2014

Large scale semi-supervised learning using KSC based model.
Proceedings of the 2014 International Joint Conference on Neural Networks, 2014

Optimal reduced sets for sparse kernel spectral clustering.
Proceedings of the 2014 International Joint Conference on Neural Networks, 2014

SVD truncation schemes for fixed-size kernel models.
Proceedings of the 2014 International Joint Conference on Neural Networks, 2014

Optimal Data Projection for Kernel Spectral Clustering.
Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014

Agglomerative hierarchical kernel spectral clustering for large scale networks.
Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014

Reweighted l1 Dual Averaging Approach for Sparse Stochastic Learning.
Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014

Gene interaction networks boost genetic algorithm performance in biomarker discovery.
Proceedings of the 2014 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making, 2014

Agglomerative hierarchical kernel spectral data clustering.
Proceedings of the 2014 IEEE Symposium on Computational Intelligence and Data Mining, 2014

Clustering data over time using kernel spectral clustering with memory.
Proceedings of the 2014 IEEE Symposium on Computational Intelligence and Data Mining, 2014

Alarm prediction in industrial machines using autoregressive LS-SVM models.
Proceedings of the 2014 IEEE Symposium on Computational Intelligence and Data Mining, 2014

New bilinear formulation to semi-supervised classification based on Kernel Spectral Clustering.
Proceedings of the 2014 IEEE Symposium on Computational Intelligence and Data Mining, 2014

High level high performance computing for multitask learning of time-varying models.
Proceedings of the 2014 IEEE Symposium on Computational Intelligence in Big Data, 2014

Representative subsets for big data learning using k-NN graphs.
Proceedings of the 2014 IEEE International Conference on Big Data, 2014

2013
Hinging Hyperplanes for Time-Series Segmentation.
IEEE Trans. Neural Networks Learn. Syst., 2013

Stability of Coupled Local Minimizers Within the Lagrange Programming Network Framework.
IEEE Trans. Circuits Syst. I Regul. Pap., 2013

FURS: Fast and Unique Representative Subset selection retaining large-scale community structure.
Social Netw. Analys. Mining, 2013

Support vector machines with piecewise linear feature mapping.
Neurocomputing, 2013

Risk group detection and survival function estimation for interval coded survival methods.
Neurocomputing, 2013

Load forecasting using a multivariate meta-learning system.
Expert Syst. Appl., 2013

Kernel Spectral Clustering for Big Data Networks.
Entropy, 2013

Learning Tensors in Reproducing Kernel Hilbert Spaces with Multilinear Spectral Penalties.
CoRR, 2013

The skweezee system: enabling the design and the programming of squeeze interactions.
Proceedings of the 26th Annual ACM Symposium on User Interface Software and Technology, 2013

Highly Sparse Reductions to Kernel Spectral Clustering.
Proceedings of the Pattern Recognition and Machine Intelligence, 2013

Weighted Coordinate-Wise Pegasos.
Proceedings of the Pattern Recognition and Machine Intelligence, 2013

Sparse Reductions for Fixed-Size Least Squares Support Vector Machines on Large Scale Data.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2013

Kernel spectral clustering for dynamic data using multiple kernel learning.
Proceedings of the 2013 International Joint Conference on Neural Networks, 2013

Non-parallel semi-supervised classification based on kernel spectral clustering.
Proceedings of the 2013 International Joint Conference on Neural Networks, 2013

Soft kernel spectral clustering.
Proceedings of the 2013 International Joint Conference on Neural Networks, 2013

Fixed-size Pegasos for hinge and pinball loss SVM.
Proceedings of the 2013 International Joint Conference on Neural Networks, 2013

Sleep apnea classification using least-squares support vector machines on single lead ECG.
Proceedings of the 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2013

Primal-Dual Framework for Feature Selection using Least Squares Support Vector Machines.
Proceedings of the 19th International Conference on Management of Data, 2013

DynOpt: Incorporating dynamics into mean-variance portfolio optimization.
Proceedings of the 2013 IEEE Conference on Computational Intelligence for Financial Engineering & Economics, 2013

Kernel spectral clustering for predicting maintenance of industrial machines.
Proceedings of the IEEE Symposium on Computational Intelligence and Data Mining, 2013

Supervised Novelty Detection.
Proceedings of the IEEE Symposium on Computational Intelligence and Data Mining, 2013

Self-tuned kernel spectral clustering for large scale networks.
Proceedings of the 2013 IEEE International Conference on Big Data, 2013

2012
Classification of Multichannel Signals With Cumulant-Based Kernels.
IEEE Trans. Signal Process., 2012

Approximate Solutions to Ordinary Differential Equations Using Least Squares Support Vector Machines.
IEEE Trans. Neural Networks Learn. Syst., 2012

Reducing the Number of Support Vectors of SVM Classifiers Using the Smoothed Separable Case Approximation.
IEEE Trans. Neural Networks Learn. Syst., 2012

Application of Kernel Principal Component Analysis for Single-Lead-ECG-Derived Respiration.
IEEE Trans. Biomed. Engineering, 2012

Confidence bands for least squares support vector machine classifiers: A regression approach.
Pattern Recognit., 2012

Optimized Data Fusion for Kernel k-Means Clustering.
IEEE Trans. Pattern Anal. Mach. Intell., 2012

Hierarchical kernel spectral clustering.
Neural Networks, 2012

Towards the detection of error-related potentials and its integration in the context of a P300 speller brain-computer interface.
Neurocomputing, 2012

A mixed effects least squares support vector machine model for classification of longitudinal data.
Comput. Stat. Data Anal., 2012

LS-SVM approximate solution to linear time varying descriptor systems.
Autom., 2012

Kernel spectral clustering for community detection in complex networks.
Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN), 2012

Robustness of kernel based regression: Influence and weight functions.
Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN), 2012

A semi-supervised formulation to binary kernel spectral clustering.
Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN), 2012

Joint Regression and Linear Combination of Time Series for Optimal Prediction.
Proceedings of the 20th European Symposium on Artificial Neural Networks, 2012

Interval coded scoring systems for survival analysis.
Proceedings of the 20th European Symposium on Artificial Neural Networks, 2012

Robust artefact detection in long-term ECG recordings based on autocorrelation function similarity and percentile analysis.
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2012

2011
Approximate Confidence and Prediction Intervals for Least Squares Support Vector Regression.
IEEE Trans. Neural Networks, 2011

Tensor Versus Matrix Completion: A Comparison With Application to Spectral Data.
IEEE Signal Process. Lett., 2011

First and Second Order SMO Algorithms for LS-SVM Classifiers.
Neural Process. Lett., 2011

A kernel-based framework to tensorial data analysis.
Neural Networks, 2011

Sparse conjugate directions pursuit with application to fixed-size kernel models.
Mach. Learn., 2011

Kernel Regression in the Presence of Correlated Errors.
J. Mach. Learn. Res., 2011

Learning Transformation Models for Ranking and Survival Analysis.
J. Mach. Learn. Res., 2011

Sparse kernel spectral clustering models for large-scale data analysis.
Neurocomputing, 2011

On the relevance of automatically selected single-voxel MRS and multimodal MRI and MRSI features for brain tumour differentiation.
Comp. in Bio. and Med., 2011

Optimized data fusion for K-means Laplacian clustering.
Bioinform., 2011

Improved performance on high-dimensional survival data by application of Survival-SVM.
Bioinform., 2011

Support vector methods for survival analysis: a comparison between ranking and regression approaches.
Artif. Intell. Medicine, 2011

Modularity-based model selection for kernel spectral clustering.
Proceedings of the 2011 International Joint Conference on Neural Networks, 2011

Out-of-sample eigenvectors in kernel spectral clustering.
Proceedings of the 2011 International Joint Conference on Neural Networks, 2011

Automatic Seizure Detection Incorporating Structural Information.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2011, 2011

Symbolic computing of LS-SVM based models.
Proceedings of the ESANN 2011, 2011

Sparse LS-SVMs with L0 - norm minimization.
Proceedings of the ESANN 2011, 2011

2010
Improved dual decomposition based optimization for DSL dynamic spectrum management.
IEEE Trans. Signal Process., 2010

Coupled Simulated Annealing.
IEEE Trans. Syst. Man Cybern. Part B, 2010

Multiway Spectral Clustering with Out-of-Sample Extensions through Weighted Kernel PCA.
IEEE Trans. Pattern Anal. Mach. Intell., 2010

Robustness of reweighted Least Squares Kernel Based Regression.
J. Multivar. Anal., 2010

Optimized fixed-size kernel models for large data sets.
Comput. Stat. Data Anal., 2010

L2-norm multiple kernel learning and its application to biomedical data fusion.
BMC Bioinform., 2010

Semi-supervised Learning of Sparse Linear Models in Mass Spectral Imaging.
Proceedings of the Pattern Recognition in Bioinformatics, 2010

Polynomial componentwise LS-SVM: Fast variable selection using low rank updates.
Proceedings of the International Joint Conference on Neural Networks, 2010

Kernel-Based Learning from Infinite Dimensional 2-Way Tensors.
Proceedings of the Artificial Neural Networks, 2010

Efficient adaptive filtering for smooth linear FIR models.
Proceedings of the 18th European Signal Processing Conference, 2010

On the use of a clinical kernel in survival analysis.
Proceedings of the ESANN 2010, 2010

Highly sparse kernel spectral clustering with predictive out-of-sample extensions.
Proceedings of the ESANN 2010, 2010

Improved non-parametric sparse recovery with data matched penalties.
Proceedings of the 2nd International Workshop on Cognitive Information Processing, 2010

Fast primal-dual projected linear iterations for distributed consensus in constrained convex optimization.
Proceedings of the 49th IEEE Conference on Decision and Control, 2010

Nuclear norm regularization for overparametrized Hammerstein systems.
Proceedings of the 49th IEEE Conference on Decision and Control, 2010

Linear parametric noise models for Least Squares Support Vector Machines.
Proceedings of the 49th IEEE Conference on Decision and Control, 2010

2009
Least conservative support and tolerance tubes.
IEEE Trans. Inf. Theory, 2009

P300 Detection Based on Feature Extraction in On-line Brain-Computer Interface.
Proceedings of the KI 2009: Advances in Artificial Intelligence, 2009

Feature Selection in Survival Least Squares Support Vector Machines with Maximal Variation Constraints.
Proceedings of the Bio-Inspired Systems: Computational and Ambient Intelligence, 2009

A regularized formulation for spectral clustering with pairwise constraints.
Proceedings of the International Joint Conference on Neural Networks, 2009

Feature Extraction and Classification of EEG Signals for Rapid P300 Mind Spelling.
Proceedings of the International Conference on Machine Learning and Applications, 2009

Robustness of Kernel Based Regression: A Comparison of Iterative Weighting Schemes.
Proceedings of the Artificial Neural Networks, 2009

MINLIP: Efficient Learning of Transformation Models.
Proceedings of the Artificial Neural Networks, 2009

Identifying Customer Profiles in Power Load Time Series Using Spectral Clustering.
Proceedings of the Artificial Neural Networks, 2009

An improved dual decomposition approach to DSL dynamic spectrum management.
Proceedings of the 17th European Signal Processing Conference, 2009

A dual interior-point distributed algorithm for large-scale data networks optimization.
Proceedings of the European Control Conference, 2009

Transductively Learning from Positive Examples Only.
Proceedings of the ESANN 2009, 2009

Distributed nonlinear optimal control using sequential convex programming and smoothing techniques.
Proceedings of the 48th IEEE Conference on Decision and Control, 2009

Robustness analysis for Least Squares kernel based regression: an optimization approach.
Proceedings of the 48th IEEE Conference on Decision and Control, 2009

Differentiation between brain metastases and glioblastoma multiforme based on MRI, MRS and MRSI.
Proceedings of the Twenty-Second IEEE International Symposium on Computer-Based Medical Systems, 2009

2008
Data Visualization and Dimensionality Reduction Using Kernel Maps With a Reference Point.
IEEE Trans. Neural Networks, 2008

Kernel Component Analysis Using an Epsilon-Insensitive Robust Loss Function.
IEEE Trans. Neural Networks, 2008

Application of a Smoothing Technique to Decomposition in Convex Optimization.
IEEE Trans. Autom. Control., 2008

Low rank updated LS-SVM classifiers for fast variable selection.
Neural Networks, 2008

A regularized kernel CCA contrast function for ICA.
Neural Networks, 2008

Robust triple mode MPC.
Int. J. Control, 2008

Sparse kernel models for spectral clustering using the incomplete Cholesky decomposition.
Proceedings of the International Joint Conference on Neural Networks, 2008

Proceedings of the Artificial Neural Networks, 2008

Survival SVM: a practical scalable algorithm.
Proceedings of the ESANN 2008, 2008

A proximal center-based decomposition method for multi-agent convex optimization.
Proceedings of the 47th IEEE Conference on Decision and Control, 2008

Application of the proximal center decomposition method to distributed model predictive control.
Proceedings of the 47th IEEE Conference on Decision and Control, 2008

2007
A Convex Approach to Validation-Based Learning of the Regularization Constant.
IEEE Trans. Neural Networks, 2007

Bagging Linear Sparse Bayesian Learning Models for Variable Selection in Cancer Diagnosis.
IEEE Trans. Inf. Technol. Biomed., 2007

Efficiently updating and tracking the dominant kernel principal components.
Neural Networks, 2007

Margin based Transductive Graph Cuts using Linear Programming.
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007

Partial Synchronization in oscillator Arrays with Asymmetric Coupling.
Int. J. Bifurc. Chaos, 2007

Support and Quantile Tubes
CoRR, 2007

A combined MRI and MRSI based multiclass system for brain tumour recognition using LS-SVMs with class probabilities and feature selection.
Artif. Intell. Medicine, 2007

A Risk Minimization Principle for a Class of Parzen Estimators.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Transductive Rademacher Complexities for Learning Over a Graph.
Proceedings of the Mining and Learning with Graphs, 2007

Fixed-size kernel logistic regression for phoneme classification.
Proceedings of the INTERSPEECH 2007, 2007

Variable selection by rank-one updates for least squares support vector machines.
Proceedings of the International Joint Conference on Neural Networks, 2007

Multi-class kernel logistic regression: a fixed-size implementation.
Proceedings of the International Joint Conference on Neural Networks, 2007

ICA through an LS-SVM based Kernel CCA Measure for Independence.
Proceedings of the International Joint Conference on Neural Networks, 2007

State-of-the-Art and Evolution in Public Data Sets and Competitions for System Identification, Time Series Prediction and Pattern Recognition.
Proceedings of the IEEE International Conference on Acoustics, 2007

Comparing Methods for Multi-class Probabilities in Medical Decision Making Using LS-SVMs and Kernel Logistic Regression.
Proceedings of the Artificial Neural Networks, 2007

Convex optimization for the design of learning machines.
Proceedings of the ESANN 2007, 2007

2006
Additive Regularization Trade-Off: Fusion of Training and Validation Levels in Kernel Methods.
Mach. Learn., 2006

Learning of spatiotemporal behaviour in cellular neural networks.
Int. J. Circuit Theory Appl., 2006

Spatiotemporal Pattern Formation on the ACE16K CNN Chip.
Int. J. Bifurc. Chaos, 2006

Bayesian kernel based classification for financial distress detection.
Eur. J. Oper. Res., 2006

A process model to develop an internal rating system: Sovereign credit ratings.
Decis. Support Syst., 2006

Fixed-size Least Squares Support Vector Machines: A Large Scale Application in Electrical Load Forecasting.
Comput. Manag. Sci., 2006

Multi-scroll and hypercube attractors from Josephson junctions.
Proceedings of the International Symposium on Circuits and Systems (ISCAS 2006), 2006

A Weighted Kernel PCA Formulation with Out-of-Sample Extensions for Spectral Clustering Methods.
Proceedings of the International Joint Conference on Neural Networks, 2006

2005
Subspace identification of Hammerstein systems using least squares support vector machines.
IEEE Trans. Autom. Control., 2005

Kernel based partially linear models and nonlinear identification.
IEEE Trans. Autom. Control., 2005

Min-max feedback MPC using a time-varying terminal constraint set and comments on "Efficient robust constrained model predictive control with a time-varying terminal constraint set".
Syst. Control. Lett., 2005

Primal-Dual Monotone Kernel Regression.
Neural Process. Lett., 2005

Handling missing values in support vector machine classifiers.
Neural Networks, 2005

Building sparse representations and structure determination on LS-SVM substrates.
Neurocomputing, 2005

The differogram: Non-parametric noise variance estimation and its use for model selection.
Neurocomputing, 2005

Subset based least squares subspace regression in RKHS.
Neurocomputing, 2005

Componentwise Least Squares Support Vector Machines
CoRR, 2005

M@CBETH: a microarray classification benchmarking tool.
Bioinform., 2005

Constrained linear MPC with time-varying terminal cost using convex combinations.
Autom., 2005

Identification of MIMO Hammerstein models using least squares support vector machines.
Autom., 2005

Load Forecasting Using Fixed-Size Least Squares Support Vector Machines.
Proceedings of the Computational Intelligence and Bioinspired Systems, 2005

Spatiotemporal pattern formation in the ACE16k CNN chip.
Proceedings of the International Symposium on Circuits and Systems (ISCAS 2005), 2005

Componentwise Support Vector Machines for Structure Detection.
Proceedings of the Artificial Neural Networks: Formal Models and Their Applications, 2005

M@CBETH: Optimizing Clinical Microarray Classification.
Proceedings of the Fourth International IEEE Computer Society Computational Systems Bioinformatics Conference Workshops & Poster Abstracts, 2005

2004
True random bit generation from a double-scroll attractor.
IEEE Trans. Circuits Syst. I Regul. Pap., 2004

Toward CNN chip-specific robustness.
IEEE Trans. Circuits Syst. I Regul. Pap., 2004

Benchmarking Least Squares Support Vector Machine Classifiers.
Mach. Learn., 2004

Systematic benchmarking of microarray data classification: assessing the role of non-linearity and dimensionality reduction.
Bioinform., 2004

Brain tumor classification based on long echo proton MRS signals.
Artif. Intell. Medicine, 2004

Learning from General Label Constraints.
Proceedings of the Structural, 2004

A double scroll based true random bit generator.
Proceedings of the 2004 International Symposium on Circuits and Systems, 2004

Morozov, Ivanov and Tikhonov Regularization Based LS-SVMs.
Proceedings of the Neural Information Processing, 11th International Conference, 2004

A Comparison of Pruning Algorithms for Sparse Least Squares Support Vector Machines.
Proceedings of the Neural Information Processing, 11th International Conference, 2004

Sparse LS-SVMs using additive regularization with a penalized validation criterion.
Proceedings of the ESANN 2004, 2004

2003
A support vector machine formulation to PCA analysis and its kernel version.
IEEE Trans. Neural Networks, 2003

Identification of positive real models in subspace identification by using regularization.
IEEE Trans. Autom. Control., 2003

Benchmarking state-of-the-art classification algorithms for credit scoring.
J. Oper. Res. Soc., 2003

Preoperative prediction of malignancy of ovarian tumors using least squares support vector machines.
Artif. Intell. Medicine, 2003

Variogram based noise variance estimation and its use in kernel based regression.
Proceedings of the NNSP 2003, 2003

Coupled chaotic simulated annealing processes.
Proceedings of the 2003 International Symposium on Circuits and Systems, 2003

Kernel PLS variants for regression.
Proceedings of the ESANN 2003, 2003

Bankruptcy prediction with least squares support vector machine classifiers.
Proceedings of the 2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003

Classification of Ovarian Tumors Using Bayesian Least Squares Support Vector Machines.
Proceedings of the Artificial Intelligence in Medicine, 2003

2002
Multiclass LS SVMs Moderated Outputs and Coding Decoding Schemes.
Neural Process. Lett., 2002

Bayesian Framework for Least-Squares Support Vector Machine Classifiers, Gaussian Processes, and Kernel Fisher Discriminant Analysis.
Neural Computation, 2002

Weighted least squares support vector machines: robustness and sparse approximation.
Neurocomputing, 2002

Families of scroll Grid attractors.
Int. J. Bifurc. Chaos, 2002

Compactly Supported RBF Kernels for Sparsifying the Gram Matrix in LS-SVM Regression Models.
Proceedings of the Artificial Neural Networks, 2002

Robust Cross-Validation Score Function for Non-linear Function Estimation.
Proceedings of the Artificial Neural Networks, 2002

The use of LS-SVM in the classification of brain tumors based on Magnetic Resonance Spectroscopy signals.
Proceedings of the ESANN 2002, 2002

Prediction of mental development of preterm newborns at birth time using LS-SVM.
Proceedings of the ESANN 2002, 2002

Least Squares Support Vector Machines
World Scientific, ISBN: 978-981-4487-59-7, 2002

2001
Financial time series prediction using least squares support vector machines within the evidence framework.
IEEE Trans. Neural Networks, 2001

Identification of stable models in subspace identification by using regularization.
IEEE Trans. Autom. Control., 2001

Optimal control by least squares support vector machines.
Neural Networks, 2001

Improved Long-Term Temperature Prediction by Chaining of Neural Networks.
Int. J. Neural Syst., 2001

Knowledge discovery in a direct marketing case using least squares support vector machines.
Int. J. Intell. Syst., 2001

Master-Slave Synchronization of Lur'e Systems with Time-Delay.
Int. J. Bifurc. Chaos, 2001

Intelligence and Cooperative Search by Coupled Local Minimizers.
Int. J. Bifurc. Chaos, 2001

Support Vector Machines: A Nonlinear Modelling and Control Perspective.
Eur. J. Control, 2001

Kernel Canonical Correlation Analysis and Least Squares Support Vector Machines.
Proceedings of the Artificial Neural Networks, 2001

Automatic relevance determination for Least Squares Support Vector Machines classifiers.
Proceedings of the ESANN 2001, 2001

2000
Robust local stability of multilayer recurrent neural networks.
IEEE Trans. Neural Networks Learn. Syst., 2000

Chaos Synchronization: a Lagrange Programming Network Approach.
Int. J. Bifurc. Chaos, 2000

Knowledge Discovery Using Least Squares Support Vector Machine Classifiers: A Direct Marketing Case.
Proceedings of the Principles of Data Mining and Knowledge Discovery, 2000

An empirical assessment of kernel type performance for least squares support vector machine classifiers.
Proceedings of the Fourth International Conference on Knowledge-Based Intelligent Information Engineering Systems & Allied Technologies, 2000

Sparse approximation using least squares support vector machines.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2000

The K.U.Leuven competition data: a challenge for advanced neural network techniques.
Proceedings of the ESANN 2000, 2000

Sparse least squares Support Vector Machine classifiers.
Proceedings of the ESANN 2000, 2000

1999
Training multilayer perceptron classifiers based on a modified support vector method.
IEEE Trans. Neural Networks, 1999

Lur'e systems with multilayer perceptron and recurrent neural networks: absolute stability and dissipativity.
IEEE Trans. Autom. Control., 1999

Least Squares Support Vector Machine Classifiers.
Neural Process. Lett., 1999

Chaos control using least‐squares support vector machines.
Int. J. Circuit Theory Appl., 1999

On the realization of n-scroll attractors.
Proceedings of the 1999 International Symposium on Circuits and Systems, ISCAS 1999, Orlando, Florida, USA, May 30, 1999

Continuous time NLq theory: absolute stability criteria.
Proceedings of the International Joint Conference Neural Networks, 1999

Multiclass least squares support vector machines.
Proceedings of the International Joint Conference Neural Networks, 1999

1998
On-Line Learning Fokker-Planck Machine.
Neural Process. Lett., 1998

Application of NL<sub>q</sub> Neural Control Theory to a Ball and Beam System.
Eur. J. Control, 1998

Improved generalization ability of neurocontrollers by imposing NLq stability constraints.
Proceedings of the ESANN 1998, 1998

1997
NL<sub>q</sub> theory: checking and imposing stability of recurrent neural networks for nonlinear modeling.
IEEE Trans. Signal Process., 1997

NL<sub>q</sub> Theory: A Neural Control Framework with Global Asymptotic Stability Criteria.
Neural Networks, 1997

Robust NL/sub q/ neural control theory.
Proceedings of International Conference on Neural Networks (ICNN'97), 1997

1996
Modelling the Belgian Gas Consumption Using Neural Networks.
Neural Process. Lett., 1996

Discrete Time Interconnected Cellular Neural Networks Within NLq Theory.
Int. J. Circuit Theory Appl., 1996

Artificial neural networks for modelling and control of non-linear systems.
Kluwer, ISBN: 978-0-7923-9678-9, 1996

1995
Generalized Cellular Neural Networks Represented in he NL<i><sub>q</sub></i> Framework.
Proceedings of the 1995 IEEE International Symposium on Circuits and Systems, ISCAS 1995, Seattle, Washington, USA, April 30, 1995

On the identification of a chaotic system by means of recurrent neural state space models.
Proceedings of International Conference on Neural Networks (ICNN'95), Perth, WA, Australia, November 27, 1995

Global asymptotic stability criteria for multilayer recurrent neural networks with applications to modelling and control.
Proceedings of International Conference on Neural Networks (ICNN'95), Perth, WA, Australia, November 27, 1995

NLq theory: unifications in the theory of neural networks, systems and control.
Proceedings of the ESANN 1995, 1995

1994
Static and dynamic stabilizing neural controllers, applicable to transition between equilibrium points.
Neural Networks, 1994