Johan A. K. Suykens

Author Info

Name	Affiliation	Papers
JOHAN A. K. SUYKENS	Katholieke Univ Leuven, Dept Elect Engn, Stadius Ctr Dynam Syst Signal Proc & Data Analyt, B-3001 Leuven, Belgium	46
Collaborators	Citations	PageRank
62	635	53.51
Referers	Referees	References
1335	684	468

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Publications (46 rows)

Collaborators (62 rows)

Referers (100 rows)

Referees (100 rows)

Title	Citations	PageRank	Year
Learning from partially labeled data.	0	0.34	2020
Robust Gradient Learning With Applications.	3	0.39	2016
Very Sparse LSSVM Reductions for Large-Scale Data.	21	0.69	2015
A Partan-Accelerated Frank-Wolfe Algorithm For Large-Scale Svm Classification	1	0.35	2015
Noise Level Estimation for Model Selection in Kernel PCA Denoising.	9	0.56	2015
New bilinear formulation to semi-supervised classification based on Kernel Spectral Clustering	0	0.34	2014
High level high performance computing for multitask learning of time-varying models	4	0.49	2014
Optimal reduced sets for sparse kernel spectral clustering	2	0.38	2014
Large scale semi-supervised learning using KSC based model	7	0.45	2014
Gene interaction networks boost genetic algorithm performance in biomarker discovery	0	0.34	2014
Alarm prediction in industrial machines using autoregressive LS-SVM models	1	0.36	2014
Multi-Class Supervised Novelty Detection	15	0.54	2014
Agglomerative hierarchical kernel spectral data clustering	1	0.39	2014
Representative subsets for big data learning using k-NN graphs	8	0.52	2014
Clustering data over time using kernel spectral clustering with memory	1	0.35	2014
Improved Initialization for Nonlinear State-Space Modeling	8	0.55	2014
DynOpt: Incorporating dynamics into mean-variance portfolio optimization	0	0.34	2013
Supervised Novelty Detection	3	0.38	2013
Self-tuned kernel spectral clustering for large scale networks	14	0.65	2013
Kernel spectral clustering for predicting maintenance of industrial machines	5	0.71	2013
Reducing the Number of Support Vectors of SVM Classifiers Using the Smoothed Separable Case Approximation	51	2.11	2012
A semi-supervised formulation to binary kernel spectral clustering	10	0.54	2012
Out-of-sample eigenvectors in kernel spectral clustering	5	0.48	2011
Approximate confidence and prediction intervals for least squares support vector regression.	32	1.70	2011
Linear parametric noise models for Least Squares Support Vector Machines	2	0.43	2010
Polynomial componentwise LS-SVM: Fast variable selection using low rank updates	0	0.34	2010
Multiway Spectral Clustering with Out-of-Sample Extensions through Weighted Kernel PCA	88	3.61	2010
Fast primal-dual projected linear iterations for distributed consensus in constrained convex optimization	3	0.43	2010
Improved non-parametric sparse recovery with data matched penalties	0	0.34	2010
Efficient adaptive filtering for smooth linear FIR models	2	0.49	2010
Coupled Simulated Annealing	60	2.91	2010
A dual interior-point distributed algorithm for large-scale data networks optimization	0	0.34	2009
An improved dual decomposition approach to DSL dynamic spectrum management	2	0.43	2009
Robustness analysis for Least Squares kernel based regression: an optimization approach	3	0.38	2009
A Convex Approach to Validation-Based Learning of the Regularization Constant	5	0.42	2007
Multi-class kernel logistic regression: a fixed-size implementation	13	0.78	2007
Interpolation based robust MPC with exact constraint handling	4	0.45	2005
Partially linear models and least squares support vector machines	7	0.89	2004
Toward CNN chip-specific robustness	14	0.99	2004
Coupled chaotic simulated annealing processes	6	0.60	2003
A support vector machine formulation to PCA analysis and its kernel version.	48	3.44	2003
Sparse approximation using least squares support vector machines	86	5.82	2000
Multiclass least squares support vector machines	53	8.94	1999
On the realization of n-scroll attractors	6	3.78	1999
Training multilayer perceptron classifiers based on a modified support vector method.	32	3.42	1999
Generalized cellular neural networks represented in the NLq framework	0	0.34	1995