Steven Van Vaerenbergh

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Ignacio SantamariaProfessor, Electrical Engineering, University of CantabriaVerified email at unican.es
Javier VíaUniversidad de CantabriaVerified email at gtas.dicom.unican.es
Miguel Lázaro-GredillaVP of research, Vicarious AIVerified email at vicarious.com
Simone ScardapaneAssistant Professor, Sapienza UniversityVerified email at uniroma1.it
Aurelio UnciniProfessor of Electrical and Computer Engineering, Sapienza University of RomeVerified email at uniroma1.it
Simone TotaroUdeM / MilaVerified email at mila.quebec
Danilo ComminielloAssociate Professor at Sapienza University of RomeVerified email at uniroma1.it
Víctor ElviraReader in Statistics and Data Science, University of EdinburghVerified email at ed.ac.uk
Fernando Perez-CruzChief Data Scientist Swiss Data Science Center and Professor T. at ETHZ--CSVerified email at sdsc.ethz.ch
Juan José Murillo FuentesFull Professor, Universidad de SevillaVerified email at us.es
jose principeprofessor of ECE, U. of FloridaVerified email at cnel.ufl.edu
Weifeng LiuUniversity of FloridaVerified email at cnel.ufl.edu
Neil D. LawrenceUniversity of CambridgeVerified email at cl.cam.ac.uk
Jesus Fernandez-BesBSICoS Group, i3a, University of ZaragozaVerified email at unizar.es
Luis A. Azpicueta-RuizUniversidad Carlos III de MadridVerified email at tsc.uc3m.es
David RamírezAssociate Professor, Universidad Carlos III de MadridVerified email at uc3m.es
M. Pilar VélezUniversidad Antonio de NebrijaVerified email at nebrija.es
Prof Amir HussainSchool of Computing, Edinburgh Napier University, Scotland, UKVerified email at napier.ac.uk
Sohan SethSenior Data Scientist, University of EdinburghVerified email at inf.ed.ac.uk
Louis ScharfResearch Professor of Mathematics, Colorado State UniversityVerified email at engr.colostate.edu

Steven Van Vaerenbergh

Assistant professor, University of Cantabria

Verified email at unican.es - Homepage

signal processing machine learning mathematics education


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Kernel recursive least-squares tracker for time-varying regression S Van Vaerenbergh, M Lázaro-Gredilla, I Santamaría IEEE transactions on neural networks and learning systems 23 (8), 1313-1326, 2012	183	2012
A sliding-window kernel RLS algorithm and its application to nonlinear channel identification S Van Vaerenbergh, J Via, I Santamaría 2006 IEEE International Conference on Acoustics Speech and Signal Processing …, 2006	171	2006
Gaussian processes for nonlinear signal processing: An overview of recent advances F Pérez-Cruz, S Van Vaerenbergh, JJ Murillo-Fuentes, M Lázaro-Gredilla, ... IEEE Signal Processing Magazine 30 (4), 40-50, 2013	146	2013
Fixed-budget kernel recursive least-squares S Van Vaerenbergh, I Santamaría, W Liu, JC Príncipe 2010 IEEE International Conference on Acoustics, Speech and Signal …, 2010	110	2010
Overlapping mixtures of Gaussian processes for the data association problem M Lázaro-Gredilla, S Van Vaerenbergh, ND Lawrence Pattern recognition 45 (4), 1386-1395, 2012	95	2012
Nonlinear System Identification using a New Sliding-Window Kernel RLS Algorithm S Van Vaerenbergh, J Via, I Santamaria JCM 2 (3), 1-8, 2007	64	2007
Kafnets: Kernel-based non-parametric activation functions for neural networks S Scardapane, S Van Vaerenbergh, S Totaro, A Uncini Neural Networks 110, 19-32, 2019	60	2019
A comparative study of kernel adaptive filtering algorithms S Van Vaerenbergh, I Santamaría 2013 IEEE Digital Signal Processing and Signal Processing Education Meeting …, 2013	52	2013
Kernel Methods for Nonlinear Identification, Equalization and Separation of Signals S Van Vaerenbergh Universidad de Cantabria, 2010	51	2010
Complex-valued neural networks with nonparametric activation functions S Scardapane, S Van Vaerenbergh, A Hussain, A Uncini IEEE Transactions on Emerging Topics in Computational Intelligence 4 (2 …, 2018	42	2018
Blind identification of SIMO Wiener systems based on kernel canonical correlation analysis S Van Vaerenbergh, J Via, I Santamaria IEEE Transactions on Signal Processing 61 (9), 2219-2230, 2013	40	2013
Estimation of the forgetting factor in kernel recursive least squares S Van Vaerenbergh, I Santamaría, M Lázaro-Gredilla 2012 IEEE International Workshop on Machine Learning for Signal Processing, 1-6, 2012	39	2012
A spectral clustering approach to underdetermined postnonlinear blind source separation of sparse sources S Van Vaerenbergh, I Santamaría IEEE Transactions on Neural Networks 17 (3), 811-814, 2006	33	2006
A probabilistic least-mean-squares filter J Fernandez-Bes, V Elvira, S Van Vaerenbergh 2015 IEEE International Conference on Acoustics, Speech and Signal …, 2015	24	2015
A Bayesian approach to tracking with kernel recursive least-squares M Lázaro-Gredilla, S Van Vaerenbergh, I Santamaría 2011 IEEE International Workshop on Machine Learning for Signal Processing, 1-6, 2011	23	2011
Adaptive kernel canonical correlation analysis algorithms for nonparametric identification of Wiener and Hammerstein systems S Van Vaerenbergh, J Via, I Santamaria EURASIP Journal on Advances in Signal Processing 2008, 1-13, 2008	21	2008
Kernel-based identification of Hammerstein systems for nonlinear acoustic echo-cancellation S Van Vaerenbergh, LA Azpicueta-Ruiz 2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014	17	2014
Semi-supervised handwritten digit recognition using very few labeled data S Van Vaerenbergh, I Santamaria, PE Barbano 2011 IEEE International Conference on Acoustics, Speech and Signal …, 2011	15	2011
Online regression with kernels S Van Vaerenbergh, I Santamaría Regularization, Optimization, Kernels, and Support Vector Machines, 477-501, 2014	14	2014
A split kernel adaptive filtering architecture for nonlinear acoustic echo cancellation S Van Vaerenbergh, LA Azpicueta-Ruiz, D Comminiello 2016 24th European Signal Processing Conference (EUSIPCO), 1768-1772, 2016	13	2016

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