Homepage of Steven Van Vaerenbergh
Welcome
I am currently a postdoctoral researcher at the GTAS group (Advanced Signal Processing Group / Grupo de Tratamiento Avanzado de Señal), Dept. of Communications Engineering, University of Cantabria, Spain. My research interests include online learning, kernel methods, Gaussian processes, canonical correlation analysis, and their application to communications problems (adaptive filtering, tracking source separation, system identification and equalization).
Code packages and toolboxes
- Kernel Methods Toolbox (KMBOX): a Matlab toolbox for nonlinear signal processing and machine learning. Includes KPCA, KCCA, KRLS and KRR code.
- KCCA package: a Matlab package for kernel canonical correlation analysis, extracted from KMBOX.
Selected publications
Journal publications:
- Steven Van Vaerenbergh, Miguel Lázaro-Gredilla and Ignacio Santamaría, "Kernel Recursive Least-Squares Tracker
for Time-Varying Regression," IEEE Transactions on Neural Networks and Learning Systems, 2012. Accepted for publication.
- Miguel Lázaro-Gredilla, Steven Van Vaerenbergh and Neil D. Lawrence, "Overlapping Mixtures of Gaussian Processes for the data association problem," Pattern Recognition, 2012. 10.1016/j.patcog.2011.10.004.
pdf version,
bibTeX entry,
Matlab source code
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Steven Van Vaerenbergh, Javier Vía, and Ignacio Santamaría, "Adaptive Kernel Canonical Correlation Analysis Algorithms for Nonparametric Identification of Wiener and Hammerstein Systems," EURASIP Journal on Advances in Signal Processing, vol. 2008, Article ID 875351, 13 pages, 2008. doi:10.1155/2008/875351.
Available online at Hindawi,
bibTeX entry
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S. Van Vaerenbergh, J. Via and I. Santamaria, "Nonlinear System Identification using a New Sliding-Window Kernel RLS Algorithm", Journal of Communications, Vol. 2, No. 3, pp. 1-8, May 2007.
Available online at JCM,
bibTeX entry
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S. Van Vaerenbergh and I. Santamaria, "A Spectral Clustering Approach to
Underdetermined Post-Nonlinear Blind Source Separation of Sparse Sources", IEEE Transactions on Neural Networks, Vol. 17, No. 3, pp. 811-814, May 2006.
pdf version,
html version
bibTeX entry
Conference publications:
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M. Lázaro-Gredilla, S. Van Vaerenbergh and I. Santamaría, "A Bayesian Approach to Tracking with Kernel Recursive Least-Squares",
IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2011), Beijing, China, September, 2011.
pdf version,
html version,
bibTeX entry,
Matlab source code
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S. Van Vaerenbergh, I. Santamaría, and P.E. Barbano, "Semi-Supervised Handwritten Digit Recognition Using Very Few Labeled Data",
IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP,
Prague, Czech Republic, May, 2011.
pdf version,
bibTeX entry,
Matlab source code
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S. Van Vaerenbergh, I. Santamaria, W. Liu and J.C. Principe, "Fixed-Budget Kernel Recursive Least-Squares",
IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP,
Dallas, Texas, March, 2010.
pdf version,
html version,
bibTeX entry
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S. Van Vaerenbergh, I. Santamaría, P.E. Barbano, U. Ozertem and D. Erdogmus, "Path-Based Spectral Clustering for Decoding Fast Time-Varying MIMO Channels",
2009 International Workshop on Machine Learning for Signal Processing (MLSP), Grenoble, France, September, 2009.
pdf version
bibTeX entry
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S. Van Vaerenbergh, J. Vía and I. Santamaría, "A Kernel Canonical Correlation Analysis Algorithm for Blind Equalization of Oversampled Wiener Systems",
IEEE International Workshop on Machine Learning for Signal Processing (MLSP 08), Cancún, Mexico, October, 2008.
pdf version,
bibTeX entry
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S. Van Vaerenbergh, E. Estébanez and I. Santamaria, "A Spectral Clustering Algorithm for Decoding Fast Time-Varying BPSK MIMO Channels",
15th European Signal Processing Conference (EUSIPCO 2007),
Poznan, Poland, September, 2007. Winner of the Best Student Paper Award
pdf version,
html version,
bibTeX entry
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S. Van Vaerenbergh, J. Via and I. Santamaria, "Online Kernel Canonical Correlation Analysis for Supervised Equalization of Wiener Systems",
International Joint Conference on Neural Networks (IJCNN 2006),
Vancouver, Canada, July 16 - 21, 2006.
pdf version,
html version,
bibTeX entry
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S. Van Vaerenbergh, J. Via and I. Santamaria, "A Sliding Window
Kernel RLS Algorithm and its Application to Nonlinear Channel Identification",
IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP,
Toulouse, France, May 15 - 19, 2006.
pdf version,
html version,
bibTeX entry
Ph.D. Dissertation:
Steven Van Vaerenbergh, "Kernel Methods for Nonlinear Identification, Equalization and Separation of Signals," University of Cantabria, 2010.
pdf version,
bibTeX entry
Book Chapters:
Steven Van Vaerenbergh and Ignacio Santamaría, "A Spectral Clustering Approach for Blind Decoding of MIMO Transmissions over Time-Correlated Fading Channels," Intelligent Systems: Techniques and Applications, Evor Hines et. al (Eds.), Shaker Publishing, Maastricht, The Netherlands, 2008.
bibTeX entry
Contact me
Steven Van Vaerenbergh
Grupo de Tratamiento Avanzado de Señal
Departamiento de Ingenieria de Comunicaciones
Laboratorios de I+D+i de Telecomunicaciones
University of Cantabria
Plaza de la Ciencia s/n - 39005 Santander - Spain
tel: 0034 942 200919 ext 802
email: steven #at# gtas.dicom.unican.es
my page at my research group: www.gtas.dicom.unican.es/members/steven
more things I do can be found at www.squobble.com