Johan Suykens | Academic Influence

Johan Suykens's AcademicInfluence.com Rankings

Johan Suykens

Engineering

#2084

World Rank

#2927

Historical Rank

Applied Physics

#238

World Rank

#248

Historical Rank

Electrical Engineering

#336

World Rank

#380

Historical Rank

engineering Degrees

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Engineering

Johan Suykens's Degrees

PhD Electrical Engineering KU Leuven
Masters Electrical Engineering KU Leuven
Bachelors Electrical Engineering KU Leuven

Why Is Johan Suykens Influential?

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According to Wikipedia, Johan Suykens is a full professor from KU Leuven in Belgium. He was named a Fellow of the Institute of Electrical and Electronics Engineers in 2015 for developing least squares support vector machines.

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Johan Suykens's Published Works

Number of citations in a given year to any of this author's works

Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author

Published Works

Least Squares Support Vector Machine Classifiers (1999) (8579)
Least Squares Support Vector Machines (2002) (1840)
Benchmarking state-of-the-art classification algorithms for credit scoring (2003) (1281)
Weighted least squares support vector machines: robustness and sparse approximation (2002) (1191)
Optimal control by least squares support vector machines (2001) (522)
Financial time series prediction using least squares support vector machines within the evidence framework (2001) (519)
Benchmarking Least Squares Support Vector Machine Classifiers (2004) (503)
Recurrent least squares support vector machines (2000) (332)
Sparse approximation using least squares support vector machines (2000) (328)
Generation of n-double scrolls (n=1, 2, 3, 4,...) (1993) (322)
Bayesian Framework for Least-Squares Support Vector Machine Classifiers, Gaussian Processes, and Kernel Fisher Discriminant Analysis (2002) (302)
True random bit generation from a double-scroll attractor (2004) (291)
Coupled Simulated Annealing (2010) (283)
Artificial neural networks for modelling and control of non-linear systems (1995) (272)
Families of scroll Grid attractors (2002) (272)
Least squares support vector machine classifiers: a large scale algorithm (1999) (268)
A tutorial on support vector machine-based methods for classification problems in chemometrics. (2010) (262)
Master-Slave Synchronization of Lur'e Systems with Time-Delay (2001) (232)
Multiway Spectral Clustering with Out-of-Sample Extensions through Weighted Kernel PCA (2010) (222)
Optimized Data Fusion for Kernel k-Means Clustering (2012) (214)
Systematic benchmarking of microarray data classification: assessing the role of non-linearity and dimensionality reduction (2004) (208)
Learning with tensors: a framework based on convex optimization and spectral regularization (2014) (206)
Bayesian kernel based classification for financial distress detection (2006) (204)
Identification of MIMO Hammerstein models using least squares support vector machines (2005) (195)
Nonlinear modeling : advanced black-box techniques (1998) (193)
LS-SVMlab : a MATLAB / C toolbox for Least Squares Support Vector Machines (2007) (192)
Robust synthesis for master-slave synchronization of Lur'e systems (1999) (192)
Brain tumor classification based on long echo proton MRS signals (2004) (189)
Application of a Smoothing Technique to Decomposition in Convex Optimization (2008) (188)
Support Vector Machines: A Nonlinear Modelling and Control Perspective (2001) (185)
Classification of brain tumours using short echo time 1H MR spectra. (2004) (182)
Subspace identification of Hammerstein systems using least squares support vector machines (2005) (181)
Concurrent monitoring of operating condition deviations and process dynamics anomalies with slow feature analysis (2015) (181)
Advances in learning theory : methods, models and applications (2003) (181)
Handling missing values in support vector machine classifiers (2005) (180)
Multiclass least squares support vector machines (1999) (178)
LS-SVMlab Toolbox User's Guide version 1.7 (2003) (177)
Transductive LSTM for time-series prediction: An application to weather forecasting (2020) (175)
Experimental confirmation of 3- and 5-scroll attractors from a generalized Chua's circuit (2000) (169)
A family of n-scroll attractors from a generalized Chua's circuit (1997) (166)
Robust nonlinear H/sub /spl infin// synchronization of chaotic Lur'e systems (1997) (163)
The efficient computation of polyhedral invariant sets for linear systems with polytopic uncertainty (2005) (162)
Artificial Neural Networks for Modeling and Control of Non-Linear Systems (1995) (158)
Tensor Versus Matrix Completion: A Comparison With Application to Spectral Data (2011) (155)
LS-SVMlab Toolbox User's Guide (2010) (153)
Support Vector Machine Classifier With Pinball Loss (2014) (152)
A support vector machine formulation to PCA analysis and its kernel version (2003) (149)
IEEE Transactions on Circuits and Systems II: Express Briefs (2004) (147)
Deep-learning neural-network architectures and methods: Using component-based models in building-design energy prediction (2018) (145)
Sparse least squares Support Vector Machine classifiers (2000) (144)
Knowledge discovery in a direct marketing case using least squares support vector machines (2001) (139)
Multiproject–multicenter evaluation of automatic brain tumor classification by magnetic resonance spectroscopy (2008) (135)
Support vector methods for survival analysis: a comparison between ranking and regression approaches (2011) (135)
Nuclear Norms for Tensors and Their Use for Convex Multilinear Estimation (2011) (133)
Robust Nonlinear H Synchronization of Chaotic Lur'e Systems (1997) (128)
Approximate Confidence and Prediction Intervals for Least Squares Support Vector Regression (2011) (128)
Electric Load Forecasting (2007) (128)
L2-norm multiple kernel learning and its application to biomedical data fusion (2010) (121)
An absolute stability criterion for the Lur'e problem with sector and slope restricted nonlinearities (1998) (119)
Application of Kernel Principal Component Analysis for Single-Lead-ECG-Derived Respiration (2012) (118)
Least squares support vector machines for classification and nonlinear modelling (2000) (114)
Cluster synchronization in oscillatory networks. (2008) (112)
Optimized fixed-size kernel models for large data sets (2010) (109)
Fixed-size Least Squares Support Vector Machines: A Large Scale Application in Electrical Load Forecasting (2006) (108)
Convex Clustering Shrinkage (2005) (103)
Identification of stable models in subspace identification by using regularization (2001) (99)
Cellular Neural Networks, Multi-Scroll Chaos and Synchronization (2005) (98)
Kernel based partially linear models and nonlinear identification (2005) (98)
n-scroll chaos generators: a simple circuit model (2001) (97)
Automatic relevance determination for Least Squares Support Vector Machines classifiers (2001) (97)
A combined MRI and MRSI based multiclass system for brain tumour recognition using LS-SVMs with class probabilities and feature selection (2007) (96)
Training multilayer perceptron classifiers based on a modified support vector method (1999) (93)
A kernel-based framework to tensorial data analysis (2011) (93)
The use of multivariate MR imaging intensities versus metabolic data from MR spectroscopic imaging for brain tumour classification. (2005) (92)
Global optimization by coupled local minimizers and its application to FE model updating (2003) (91)
Reducing the Number of Support Vectors of SVM Classifiers Using the Smoothed Separable Case Approximation (2012) (90)
Learning with the maximum correntropy criterion induced losses for regression (2015) (90)
Master-slave synchronization using dynamic output feedback (1997) (83)
A kernel-based integration of genome-wide data for clinical decision support (2009) (83)
Interior-Point Lagrangian Decomposition Method for Separable Convex Optimization (2009) (82)
Nonlinear system identification using neural state space models, applicable to robust control design (1995) (82)
Impulsive Synchronization of Chaotic Lur'e Systems by Measurement Feedback (1998) (82)
Interpolation based MPC for LPV systems using polyhedral invariant sets (2005) (81)
EnsembleSVM: a library for ensemble learning using support vector machines (2014) (81)
Support vector machines for survival analysis (2007) (80)
Preoperative prediction of malignancy of ovarian tumors using least squares support vector machines (2003) (79)
A robust ensemble approach to learn from positive and unlabeled data using SVM base models (2014) (78)
Lur'e systems with multilayer perceptron and recurrent neural networks: absolute stability and dissipativity (1999) (77)
Nosologic imaging of the brain: segmentation and classification using MRI and MRSI (2009) (77)
Model Selection in Kernel Based Regression using the Influence Function (2008) (76)
Intelligence and Cooperative Search by Coupled Local Minimizers (2002) (75)
n-Double Scroll Hypercubes in 1-D CNNs (1997) (75)
Ramp loss linear programming support vector machine (2014) (74)
Introduction to Focus Issue: synchronization in complex networks. (2008) (73)
Kernel Spectral Clustering for Big Data Networks (2013) (72)
Load forecasting using a multivariate meta-learning system (2013) (72)
A Comparison of Pruning Algorithms for Sparse Least Squares Support Vector Machines (2004) (72)
LS-SVM based spectral clustering and regression for predicting maintenance of industrial machines (2015) (72)
Random Features for Kernel Approximation: A Survey on Algorithms, Theory, and Beyond (2020) (70)
Absolute stability theory and master-slave synchronization (1997) (70)
A process model to develop an internal rating system: Sovereign credit ratings (2006) (68)
Subset based least squares subspace regression in RKHS (2005) (68)
Automated structural health monitoring based on adaptive kernel spectral clustering (2017) (67)
Quasilinear approach to nonlinear systems and the design of n-double scroll (n=1, 2, 3, 4, . . .) (1991) (66)
Very Sparse LSSVM Reductions for Large-Scale Data (2015) (66)
Low rank updated LS-SVM classifiers for fast variable selection (2008) (66)
Nonlinear H∞ Synchronization of Chaotic Lur'e Systems (1997) (65)
Incorporating structural information from the multichannel EEG improves patient-specific seizure detection (2012) (63)
Nonlinear system identification using neural networks (1996) (62)
Approximate Solutions to Ordinary Differential Equations Using Least Squares Support Vector Machines (2012) (62)
NLq theory: checking and imposing stability of recurrent neural networks for nonlinear modeling (1997) (61)
Robustness of Kernel Based Regression: A Comparison of Iterative Weighting Schemes (2009) (61)
Electric Load Forecasting: Using Kernel-Based Modeling for Nonlinear System Identification (2007) (61)
Multi-View Kernel Spectral Clustering (2018) (60)
A SIMPLE ALGORITHM FOR ROBUST MPC (2005) (59)
Extending Newton's law from nonlocal-in-time kinetic energy (2009) (59)
Efficiently updating and tracking the dominant kernel principal components (2007) (59)
Learning from General Label Constraints (2004) (59)
Towards the detection of error-related potentials and its integration in the context of a P300 speller brain-computer interface (2012) (58)
Least squares support vector machines classifiers : a multi two-spiral benchmark problem (2001) (58)
Genetic Weight Optimization of a Feedforward Neural Network Controller (1993) (57)
Master-Slave Synchronization of Lur'e Systems (1997) (56)
Kernel Component Analysis Using an Epsilon-Insensitive Robust Loss Function (2008) (56)
Learning solutions to partial differential equations using LS-SVM (2015) (55)
Enhancing Dynamic Soft Sensors based on DPLS: a Temporal Smoothness Regularization Approach (2015) (54)
Robust local stability of multilayer recurrent neural networks (2000) (54)
Bankruptcy prediction with least squares support vector machine classifiers (2003) (54)
Linear and Non-linear Credit Scoring by Combining Logistic Regression and Support Vector Machines (2006) (54)
A Statistical Learning Approach to Modal Regression (2017) (53)
Robust triple mode MPC (2006) (53)
Least-Squares Support Vector Machines for the Identification of Wiener-Hammerstein Systems (2012) (53)
Multiclass LS-SVMs: Moderated Outputs and Coding-Decoding Schemes (2002) (52)
Kernel Regression in the Presence of Correlated Errors (2011) (52)
Indefinite kernels in least squares support vector machines and principal component analysis (2017) (51)
Multi-agent reinforcement learning for modeling and control of thermostatically controlled loads (2019) (50)
Chaos control using least squares support vector machines (1999) (50)
Multi-class kernel logistic regression: a fixed-size implementation (2007) (50)
An empirical assessment of kernel type performance for least squares support vector machine classifiers (2000) (49)
Improved performance on high-dimensional survival data by application of Survival-SVM (2011) (49)
Multi-Class Supervised Novelty Detection (2014) (49)
Support Vector Machine Classifier With Pinball Loss. (2014) (48)
Data Visualization and Dimensionality Reduction Using Kernel Maps With a Reference Point (2008) (48)
Multiclass Semisupervised Learning Based Upon Kernel Spectral Clustering (2015) (48)
Asymmetric least squares support vector machine classifiers (2014) (48)
Multi-View Least Squares Support Vector Machines Classification (2017) (47)
Improved Dual Decomposition Based Optimization for DSL Dynamic Spectrum Management (2010) (47)
Robust Low-Rank Tensor Recovery With Regularized Redescending M-Estimator (2016) (47)
The skweezee system: enabling the design and the programming of squeeze interactions (2013) (46)
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" (2005) (45)
Nonlinear H/sub /spl infin// synchronization of Lur'e systems: dynamic output feedback case (1997) (45)
A Theoretical Framework for Target Propagation (2020) (45)
Incremental kernel spectral clustering for online learning of non-stationary data (2014) (44)
Load Forecasting Using Fixed-Size Least Squares Support Vector Machines (2005) (44)
Two-level ℓ1 minimization for compressed sensing (2015) (43)
NLq Theory: A Neural Control Framework with Global Asymptotic Stability Criteria (1997) (43)
Kernel Canonical Correlation Analysis and Least Squares Support Vector Machines (2001) (43)
Regularization, Optimization, Kernels, and Support Vector Machines (2014) (43)
Explaining Support Vector Machines: A Color Based Nomogram (2016) (42)
Application of the proximal center decomposition method to distributed model predictive control (2008) (42)
Distributed nonlinear optimal control using sequential convex programming and smoothing techniques (2009) (41)
Fast Prediction with SVM Models Containing RBF Kernels (2014) (41)
Identification of Wiener-Hammerstein Systems using LS-SVMs (2009) (40)
WINNING ENTRY OF THE K. U. LEUVEN TIME-SERIES PREDICTION COMPETITION (1999) (39)
A Mathematical Model for Interpretable Clinical Decision Support with Applications in Gynecology (2012) (38)
Sequential minimal optimization for SVM with pinball loss (2015) (38)
LS-SVM approximate solution to linear time varying descriptor systems (2012) (37)
Automatic relevance determination for least squares support vector machine regression (2001) (37)
Learning a simple recurrent neural state space model to behave like Chua's double scroll (1995) (37)
Non-parallel support vector classifiers with different loss functions (2014) (37)
Componentwise Least Squares Support Vector Machines (2005) (37)
A Rank-One Tensor Updating Algorithm for Tensor Completion (2015) (37)
Nonlinear H Synchronization of Lur ’ e Systems : Dynamic Output Feedback Case (1997) (36)
Effect of feature extraction for brain tumor classification based on short echo time 1H MR spectra (2008) (36)
Static and dynamic stabilizing neural controllers, applicable to transition between equilibrium points (1994) (36)
Identification of positive real models in subspace identification by using regularization (2003) (36)
Deep hybrid neural-kernel networks using random Fourier features (2018) (36)
Least squares support vector machines and primal space estimation (2003) (35)
Basic Methods of Least Squares Support Vector Machines (2002) (35)
Toward CNN chip-specific robustness (2004) (35)
Regularized Semipaired Kernel CCA for Domain Adaptation (2018) (35)
A mixed effects least squares support vector machine model for classification of longitudinal data (2012) (35)
Deep Restricted Kernel Machines Using Conjugate Feature Duality (2017) (35)
Does the combination of magnetic resonance imaging and spectroscopic imaging improve the classification of brain tumours? (2004) (35)
An SVD-free Approach to a Class of Structured Low Rank Matrix Optimization Problems with Application to System Identification (2013) (35)
Parameter estimation of delay differential equations: An integration-free LS-SVM approach (2014) (35)
Multilevel Hierarchical Kernel Spectral Clustering for Real-Life Large Scale Complex Networks (2014) (34)
Noise Level Estimation for Model Selection in Kernel PCA Denoising (2015) (34)
Feature Extraction and Classification of EEG Signals for Rapid P300 Mind Spelling (2009) (33)
Bagging Linear Sparse Bayesian Learning Models for Variable Selection in Cancer Diagnosis (2007) (33)
Nonparametric Regression via StatLSSVM (2013) (33)
Building sparse representations and structure determination on LS-SVM substrates (2005) (32)
Primal-Dual Monotone Kernel Regression (2005) (32)
Learning Transformation Models for Ranking and Survival Analysis (2011) (31)
Parallelized Tensor Train Learning of Polynomial Classifiers (2016) (31)
Robust Support Vector Machines for Classification with Nonconvex and Smooth Losses (2016) (30)
Representative subsets for big data learning using k-NN graphs (2014) (30)
Magnetic eigenmaps for community detection in directed networks (2016) (30)
Self-tuned kernel spectral clustering for large scale networks (2013) (30)
Support vector machines with piecewise linear feature mapping (2013) (30)
Kernel spectral clustering with memory effect (2013) (30)
Classification With Truncated $\ell _{1}$ Distance Kernel (2018) (30)
Spatio-temporal Stacked LSTM for Temperature Prediction in Weather Forecasting (2018) (29)
Survival SVM: a practical scalable algorithm (2008) (29)
Improved Long-Term Temperature Prediction by Chaining of Neural Networks (2001) (29)
P300 Detection Based on Feature Extraction in On-line Brain-Computer Interface (2009) (29)
Primal and dual model representations in kernel-based learning (2010) (28)
Subspace algorithms for system identification and stochastic realization (1991) (28)
Constrained linear MPC with time-varying terminal cost using convex combinations (2005) (28)
A regularized kernel CCA contrast function for ICA (2008) (28)
Kernelized Elastic Net Regularization: Generalization Bounds, and Sparse Recovery (2016) (28)
Kernel Spectral Clustering and applications (2015) (27)
Robust artefact detection in long-term ECG recordings based on autocorrelation function similarity and percentile analysis (2012) (27)
Rank-1 Tensor Properties with Applications to a Class of Tensor Optimization Problems (2016) (27)
Kernel regression in high dimension: Refined analysis beyond double descent (2020) (27)
A Weighted Kernel PCA Formulation with Out-of-Sample Extensions for Spectral Clustering Methods (2006) (27)
Feedback linearization of nonlinear distortion in electrodynamic loudspeakers (1995) (26)
Robustness of reweighted Least Squares Kernel Based Regression (2010) (26)
Modelling the strip thickness in hot steel rolling mills using least‐squares support vector machines (2018) (26)
First and Second Order SMO Algorithms for LS-SVM Classifiers (2011) (26)
Subspace intersection identification of Hammerstein-Wiener systems (2005) (26)
Image Segmentation using a Weighted Kernel PCA Approach to Spectral Clustering (2007) (26)
FURS: Fast and Unique Representative Subset selection retaining large-scale community structure (2013) (26)
Hierarchical kernel spectral clustering (2012) (25)
Magnetic Eigenmaps for Visualization of Directed Networks (2016) (25)
Impulsive Control and Synchronization of Chaos (1999) (25)
A Risk Minimization Principle for a Class of Parzen Estimators (2007) (25)
Transfer learning in demand response: A review of algorithms for data-efficient modelling and control (2021) (25)
Confidence bands for least squares support vector machine classifiers: A regression approach (2012) (25)
Sparse kernel spectral clustering models for large-scale data analysis (2011) (24)
Convex Formulation for Kernel PCA and Its Use in Semisupervised Learning (2016) (24)
Fixed-size Pegasos for hinge and pinball loss SVM (2013) (24)
Primal space sparse kernel partial least squares regression for large scale problems (2004) (24)
Learning Tensors in Reproducing Kernel Hilbert Spaces with Multilinear Spectral Penalties (2013) (24)
Improved Initialization for Nonlinear State-Space Modeling (2014) (24)
Optimized data fusion for K-means Laplacian clustering (2010) (23)
Neural networks for control (1996) (23)
Estimating the unknown time delay in chemical processes (2016) (23)
Short Term Chaotic Time Series Prediction using Symmetric LS-SVM Regression (2005) (23)
QoS prediction for web service compositions using kernel-based quantile estimation with online adaptation of the constant offset (2014) (23)
Fixed-Size LS-SVM Applied to the Wiener-Hammerstein Benchmark (2009) (23)
Partially linear models and least squares support vector machines (2004) (23)
Identification of the Silverbox Benchmark Using Nonlinear State-Space Models (2012) (22)
Boosting Co-teaching with Compression Regularization for Label Noise (2021) (22)
Hybrid Conditional Gradient - Smoothing Algorithms with Applications to Sparse and Low Rank Regularization (2014) (22)
Solution Path for Pin-SVM Classifiers With Positive and Negative $\tau $ Values (2017) (21)
Support Vector Machines : Least Squares Approaches and Extensions (2003) (21)
Sparse kernel models for spectral clustering using the incomplete Cholesky decomposition (2008) (21)
Sparse Reductions for Fixed-Size Least Squares Support Vector Machines on Large Scale Data (2013) (21)
A comparative study of ls-svm’s applied to the silver box identification problem (2004) (21)
Soft kernel spectral clustering (2013) (21)
Sleep apnea classification using least-squares support vector machines on single lead ECG (2013) (21)
Additive Regularization Trade-Off: Fusion of Training and Validation Levels in Kernel Methods (2006) (21)
Modelling the Belgian gas consumption using neural networks (1996) (21)
Imposing Symmetry in Least Squares Support Vector Machines Regression (2005) (21)
Parameter Estimation for Time Varying Dynamical Systems using Least Squares Support Vector Machines (2012) (21)
The differogram: Non-parametric noise variance estimation and its use for model selection (2005) (20)
The K.U.Leuven Time Series Prediction Competition (1998) (20)
Sparse LS-SVMs with L0 - norm minimization (2011) (20)
Morozov, Ivanov and Tikhonov Regularization Based LS-SVMs (2004) (20)
Numerical studies of slow rhythms emergence in neural microcircuits: bifurcations and stability. (2009) (19)
A two-experiment approach to Wiener system identification (2018) (19)
Error-related potential recorded by EEG in the context of a p300 mind speller brain-computer interface (2010) (19)
Sparse conjugate directions pursuit with application to fixed-size kernel models (2011) (19)
Side channel attacks on cryptographic devices as a classification problem (2007) (19)
Robust nonlinear H$_{\infty}$ synchronization of chaotic Lur'e systems (1997) (19)
Least Squares Support Vector Machines for Kernel CCA in Nonlinear State-Space Identification (2004) (19)
Asymmetric v-tube support vector regression (2014) (19)
Compactly Supported RBF Kernels for Sparsifying the Gram Matrix in LS-SVM Regression Models (2002) (19)
Nonlinear H$_{\infty}$ synchronization of chaotic Lur'e systems (1997) (18)
Learning of spatiotemporal behaviour in cellular neural networks (2006) (18)
Efficient hinging hyperplanes neural network and its application in nonlinear system identification (2019) (18)
LS-SVM REGRESSION WITH AUTOCORRELATED ERRORS (2006) (18)
Classification of Multichannel Signals With Cumulant-Based Kernels (2012) (17)
Time Series Prediction using LS-SVMs (2008) (17)
Hyperchaotic n-scroll attractors (2000) (17)
A double scroll based true random bit generator (2004) (17)
A novel neural grey system model with Bayesian regularization and its applications (2021) (17)
Margin based Transductive Graph Cuts using Linear Programming (2007) (17)
On the realization of n-scroll attractors (1999) (17)
Hinging Hyperplanes for Time-Series Segmentation (2013) (17)
Robust Cross-Validation Score Function for Non-linear Function Estimation (2002) (17)
A semi-supervised formulation to binary kernel spectral clustering (2012) (17)
Incremental multi-class semi-supervised clustering regularized by Kalman filtering (2015) (17)
Robust synthesis of constrained linear state feedback using LMIs and polyhedral invariant sets (2006) (16)
Identifying Customer Profiles in Power Load Time Series Using Spectral Clustering (2009) (16)
Lazy learning for iterated time-series prediction (1998) (16)
Time Series Prediction Competition (1999) (16)
Pinball Loss Minimization for One-bit Compressive Sensing (2015) (16)
Fixed-size kernel logistic regression for phoneme classification (2007) (16)
Kernel Density Estimation for Dynamical Systems (2016) (16)
On-Line Learning Fokker-Planck Machine (1998) (15)
Large scale semi-supervised learning using KSC based model (2014) (15)
Kernel spectral clustering for community detection in complex networks (2012) (15)
M@CBETH: a microarray classification benchmarking tool (2005) (15)
Fast kernel spectral clustering (2017) (15)
Coupled chaotic simulated annealing processes (2003) (15)
Variety of synchronous regimes in neuronal ensembles. (2008) (15)
Predicting breast cancer using an expression values weighted clinical classifier (2014) (15)
Consensus over Ring Networks as a Quadratic Optimal Control Problem (2010) (14)
The K.U.Leuven competition data: a challenge for advanced neural network techniques (2000) (14)
A Bayesian nonlinear support vector machine error correction model (2006) (14)
Bayesian inference for LS-SVMs on large data sets using the Nystrom method (2002) (14)
Out-of-sample eigenvectors in kernel spectral clustering (2011) (14)
Random Fourier Features via Fast Surrogate Leverage Weighted Sampling (2019) (14)
Nuclear norm regularization for overparametrized Hammerstein systems (2010) (14)
Chaotic systems synchronization (2003) (14)
Neural control theory : an overview (1996) (14)
Fast and scalable Lasso via stochastic Frank–Wolfe methods with a convergence guarantee (2015) (14)
Impulsive control of nonautonomous chaotic systems using practical stabilization (1998) (13)
Finding communities in weighted networks through synchronization. (2011) (13)
Modularity-based model selection for kernel spectral clustering (2011) (13)
Least Squares Support Vector Machines : an Overview (2002) (13)
Least squares support vector machine regression for discriminant analysis (2001) (13)
A regularized formulation for spectral clustering with pairwise constraints (2009) (13)
A MULTI PARAMETRIC QUADRATIC PROGRAMMING SOLUTION TO ROBUST PREDICTIVE CONTROL (2005) (13)
Cooperative Behavior in Coupled Simulated Annealing Processes with Variance Control (2006) (13)
Non-parallel semi-supervised classification based on kernel spectral clustering (2013) (12)
Kernel spectral clustering for predicting maintenance of industrial machines (2013) (12)
On the relevance of automatically selected single-voxel MRS and multimodal MRI and MRSI features for brain tumour differentiation (2011) (12)
An application of feature selection to on-line P300 detection in brain-computer interface (2009) (12)
Quantile regression with ℓ1—regularization and Gaussian kernels (2014) (12)
Support vector machines and kernel-based learning for dynamical systems modelling (2009) (12)
Diversity sampling is an implicit regularization for kernel methods (2020) (12)
Stability of Coupled Local Minimizers Within the Lagrange Programming Network Framework (2013) (12)
Indefinite Kernel Logistic Regression With Concave-Inexact-Convex Procedure (2019) (12)
NARX identification of hammerstein models using least squares support vector machines (2004) (12)
Ensemble Learning of Coupled Parmeterised Kernel Models (2003) (12)
Deep convolutional learning for general early design stage prediction models (2019) (11)
Impulse response constrained LS-SVM modelling for MIMO Hammerstein system identification (2019) (11)
Interpolation Based MPC with Exact Constraint Handling : the Uncertain Case (2005) (11)
Additive regularization: fusion of training and validation levels in kernel methods (2003) (11)
Hammerstein system identification through best linear approximation inversion and regularisation (2018) (11)
Highly sparse kernel spectral clustering with predictive out-of-sample extensions (2010) (11)
Component-Based Machine Learning Modelling Approach for Design Stage Building Energy Prediction: Weather Conditions and Size (2017) (11)
Improved Microarray-Based Decision Support with Graph Encoded Interactome Data (2010) (11)
Robustness analysis for Least Squares kernel based regression: an optimization approach (2009) (11)
Kernel spectral clustering for dynamic data using multiple kernel learning (2013) (10)
Clustering data over time using kernel spectral clustering with memory (2014) (10)
Multi-view LS-SVM regression for black-box temperature prediction in weather forecasting (2017) (10)
Transductive Feature Selection Using Clustering-Based Sample Entropy for Temperature Prediction in Weather Forecasting (2018) (10)
Spatiotemporal pattern formation in the ACE16k CNN chip (2005) (10)
NLq neural control theory: Case study for a ball and beam system (1997) (10)
The use of LS-SVM in the classification of brain tumors based on Magnetic Resonance Spectroscopy signals (2002) (10)
Interpolation based robust MPC with exact constraint handling (2005) (10)
Signal recovery for jointly sparse vectors with different sensing matrices (2015) (10)
Stability criteria for neural control systems (1995) (10)
Efficient evolutionary spectral clustering (2016) (9)
Automatic chip-spcific CNN template optimization using adaptive simulated Annealing (2003) (9)
Modified Frank-Wolfe Algorithm for Enhanced Sparsity in Support Vector Machine Classifiers (2017) (9)
Kernel PLS variants for regression (2003) (9)
Linear parametric noise models for Least Squares Support Vector Machines (2010) (9)
Least squares support vector machine classifiers: an empirical evaluation (2000) (9)
An Online Algorithm for Learning a Labeling of a Graph (2008) (9)
Segmentation of Time Series from Nonlinear Dynamical Systems (2011) (9)
Influence of passive elements on the dynamics of oscillatory ensembles of cardiac cells. (2009) (9)
Generative Restricted Kernel Machines: A framework for multi-view generation and disentangled feature learning (2020) (9)
Correntropy Based Matrix Completion (2018) (9)
TR-06-09 ROBUSTNESS AND STABILITY OF REWEIGHTED KERNEL BASED REGRESSION (2006) (9)
Differentiation between brain metastases and glioblastoma multiforme based on MRI, MRS and MRSI (2009) (9)
Black-box modeling for temperature prediction in weather forecasting (2015) (9)
Quadratically Constrained Quadratic Programming for Subspace Selection in Kernel Regression Estimation (2008) (9)
Indefinite kernel spectral learning (2018) (9)
Support Vector Machines and Kernel Based Learning (2005) (9)
Deformed Laplacians and spectral ranking in directed networks (2015) (9)
Higher order Matching Pursuit for Low Rank Tensor Learning (2015) (9)
Global asymptotic stability criteria for multilayer recurrent neural networks with applications to modelling and control (1995) (8)
Imposing stability in subspace identification by regularization (2000) (8)
Transductively Learning from Positive Examples Only (2009) (8)
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Fast primal-dual projected linear iterations for distributed consensus in constrained convex optimization (2010) (8)
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Learning Theory Estimates with Observations from General Stationary Stochastic Processes (2016) (8)
High level high performance computing for multitask learning of time-varying models (2014) (8)
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Bayesian input selection for nonlinear regression with LS-SVMS (2003) (8)
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Automatic Seizure Detection Incorporating Structural Information (2011) (7)
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Robust Gradient Learning With Applications (2016) (7)
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Tensor Learning in Multi-view Kernel PCA (2018) (6)
Interval coded scoring systems for survival analysis (2012) (6)
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Variable selection and grouping with multiple graph priors (2009) (6)
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Netgram: Visualizing Communities in Evolving Networks (2015) (6)
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Piecewise linear neural networks and deep learning (2022) (6)
Multi-label semi-supervised learning using regularized kernel spectral clustering (2016) (6)
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Hybrid Coupled Local Minimizers (2014) (6)
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Risk group detection and survival function estimation for interval coded survival methods (2013) (6)
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Unsupervised learning of disentangled representations in deep restricted kernel machines with orthogonality constraints (2020) (6)
Compressing Features for Learning with Noisy Labels (2022) (5)
Kernel Clustering for Knowledge Discovery in Clinical Microarray Data Analysis (2007) (5)
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Scalable Hybrid Deep Neural Kernel Networks (2017) (5)
Discrete Time Interconnected Cellular Neural Networks Within NLq Theory (1996) (5)
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The Bures Metric for Taming Mode Collapse in Generative Adversarial Networks (2020) (5)
Deep Neural Network Architectures for Component-Based Machine Learning Model in Building Energy Predictions (2017) (5)
Artificial neural networks: architectures and learning rules (1996) (5)
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Signal processing theory and machine learning (2014) (5)
Constructionof Reduced Complexity Polyhedral Invariant Sets for LPV Systems using Linear Programming (2005) (5)
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Generative Kernel PCA (2018) (5)
Robust Generative Restricted Kernel Machines using Weighted Conjugate Feature Duality (2020) (5)
Transductive Rademacher Complexities for Learning Over a Graph (2007) (5)
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SVD revisited: A new variational principle, compatible feature maps and nonlinear extensions (2016) (5)
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Generative Restricted Kernel Machines (2019) (5)
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MINLIP: Efficient Learning of Transformation Models (2009) (4)
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Polynomial componentwise LS-SVM: Fast variable selection using low rank updates (2010) (4)
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Kernel Regression with Correlated Errors (2010) (4)
Scroll maps from n-scroll attractors (2002) (4)
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Nonlinear System Modeling (1998) (4)
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Introduction to Machine Learning (2014) (4)
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3.11 – Kernel Methods (2009) (3)
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3D-Grid Scroll Attractors (2001) (2)
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Learning with Primal and Dual Model Representations: A Unifying Picture (ICASSP16 Plenary) (2016) (0)
Island Transpeciation: A Co-Evolutionary Neural Architecture Search, applied to country-scale air-quality forecasting (2022) (0)
Alpha and beta stability for additively regularized LS-SVMs via convex optimization (2004) (0)
Hierarchical semi-supervised clustering using KSC based model (2015) (0)
Identification of structured dynamical systems in tensor product reproducing kernle hilbert spaces (2014) (0)
Learning Lipschitz-smooth Utility Functions for Transformation Models in Ranking Problems (2008) (0)
RKHS, energy, discrepancy and SVM (2016) (0)
M@CBETH: optimizing clinical microarray classification (2005) (0)
An Interior Point Lagrangian Decomposition Method for Convex Programming (2009) (0)
Book and Media Review Editor (2008) (0)
Iteratively reweighted least squares support vector regression (2005) (0)
Convex optimization for the design of learning machines (2007) (0)
Bayesian Learning and the Fokker-planck Machine 1 Bayesian Learning and the Fokker-planck Machine (1998) (0)
Nonlinear H$_{\infty}$ control for continuous-time recurrent neural networks (1997) (0)
Fixed-size Kernel Models for Big Data - Part III (2015) (0)
Topranking : predicting the most relevant element of a set (2008) (0)
Nonparametric comparison of signals based on statistiscal bootstrap techniques (2006) (0)
Static and Dynamic Stabilizing Neural Controllers, Applicable to Transition between Equilibrium Points 1 (1993) (0)
Robust NL/sub q/ neural control theory (1997) (0)
Semi-Supervised Learning Using Kernel Spectral Clustering Core Model (2015) (0)
Continuous time NLq theory: absolute stability criteria (1999) (0)
Nosologic Imaging of Brain Tumors Using MRI and MRSI (2011) (0)

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What Schools Are Affiliated With Johan Suykens?

Johan Suykens is affiliated with the following schools:

KU Leuven