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Steven Van Vaerenbergh

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Thesis
Van Vaerenbergh, S., Kernel methods for nonlinear identification, equalization and separation of signals: University of Cantabria, 2010. PDF icon PDF Version (3.9 MB)
Journal Article
Van Vaerenbergh, S., and I. Santamaría, "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 icon PDF Version (163.21 KB)
Van Vaerenbergh, S., I. Santamaría, and P E. Barbano, "Semi-Supervised Object Recognition Based on Connected Image Transformations", Expert Systems with Applications, vol. 40, pp. 7069--7079, December, 2013. PDF icon PDF Version (339.82 KB)
Lázaro-Gredilla, M., S. Van Vaerenbergh, and N. D. Lawrence, "Overlapping Mixtures of Gaussian Processes for the Data Association Problem", Pattern Recognition, vol. 45, no. 4, pp. 1386–1395, April, 2012. PDF icon PDF Version (1.03 MB)
Van Vaerenbergh, S., J. Vía, and I. Santamaría, "Nonlinear System Identification using a New Sliding-Window Kernel RLS Algorithm", Journal of Communications, vol. 2, no. 3, pp. 1–8, May, 2007. PDF icon PDF Version (655.52 KB)
Ramírez, D., I. Santamaría, L. L. Scharf, and S. Van Vaerenbergh, "Multi-Channel Factor Analysis with Common and Unique Factors", IEEE Transactions on Signal Processing, vol. 68, issue 1, pp. 113-126, 2020. PDF icon PDF Version (2.53 MB)
Van Vaerenbergh, S., M. Lázaro-Gredilla, and I. Santamaría, "Kernel Recursive Least-Squares Tracker for Time-Varying Regression", IEEE Transactions on Neural Networks and Learning Systems, vol. 23, issue 8, pp. 1313--1326, August, 2012. PDF icon PDF Version (861.59 KB)
Manco-Vásquez, J., S. Van Vaerenbergh, J. Vía, and I. Santamaría, "Kernel Canonical Correlation Analysis for Robust Cooperative Spectrum Sensing in Cognitive Radio Networks", Transactions on Emerging Telecommunications Technologies, vol. 28, issue 1, 2014. PDF icon PDF Version (364.57 KB)
Scardapane, S., S. Van Vaerenbergh, S. Totaro, and A. Uncini, "Kafnets: Kernel-based non-parametric activation functions for neural networks", Neural Networks, vol. 110, pp. 19-32, February, 2019.
Pérez-Cruz, F., S. Van Vaerenbergh, J J. Murillo-Fuentes, M. Lázaro-Gredilla, and I. Santamaría, "Gaussian Processes for Nonlinear Signal Processing: An Overview of Recent Advances", IEEE Signal Processing Magazine, vol. 30, issue 4, pp. 40-50, July, 2013. PDF icon PDF Version (1.68 MB)
Lázaro-Gredilla, M., and S. Van Vaerenbergh, "A Gaussian Process Model for Data Association and a Semi-Definite Programming Solution", IEEE Transactions on Neural Networks and Learning Systems, vol. 25, issue 11, pp. 1967-1979, November, 2014. PDF icon PDF Version (394.75 KB)
Scardapane, S., S. Van Vaerenbergh, A. Hussain, and A. Uncini, "Complex-valued Neural Networks with Non-parametric Activation Functions", IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 3, issue 1, 2018.
Van Vaerenbergh, S., J. Vía, and I. Santamaría, "Blind Identification of SIMO Wiener Systems based on Kernel Canonical Correlation Analysis", IEEE Transactions on Signal Processing, vol. 61, issue 9, pp. 2219-2230, May, 2013. PDF icon PDF Version (363.45 KB)
Van Vaerenbergh, S., J. Vía, and I. Santamaría, "Adaptive kernel canonical correlation analysis algorithms for nonparametric identification of Wiener and Hammerstein systems", EURASIP Journal on Advances in Signal Processing, April, 2008. PDF icon PDF Version (884.41 KB)
Conference Paper
Van Vaerenbergh, S., D. Comminiello, and L. A. Azpicueta-Ruiz, "A Split Kernel Adaptive Filtering Architecture for Nonlinear Acoustic Echo Cancellation", 24th European Signal Processing Conference (EUSIPCO 2016), Budapest, Hungary, September, 2016. PDF icon PDF Version (374.7 KB)
Van Vaerenbergh, S., E. Estébanez, and I. Santamaría, "A Spectral Clustering Algorithm for Decoding Fast Time-Varying BPSK MIMO", 15th European Signal Processing Conference (EUSIPCO 2007), Poznan, Poland, September, 2007. PDF icon PDF Version (175.3 KB)
Van Vaerenbergh, S., J. Vía, and I. Santamaría, "A Sliding-Window Kernel RLS Algorithm and its Application to Nonlinear Channel Identification", IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2006), Toulouse, France, May, 2006. PDF icon PDF Version (186.03 KB)
Van Vaerenbergh, S., 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 2011), Prague, Czech Republic, May, 2011. PDF icon PDF Version (319.53 KB)
Van Vaerenbergh, S., J. Fernández-Bes, and V. Elvira, "On The Relationship Between Online Gaussian Process Regression And Kernel Least Mean Squares Algorithms", 2016 IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2016), Salerno, Italy, IEEE, September, 2016. PDF icon PDF Version (175.24 KB)
Van Vaerenbergh, S., S. Scardapane, and I. Santamaría, "Recursive multikernel filters exploiting nonlinear temporal structure", 25th European Signal Processing Conference (EUSIPCO 2017), Kos, Greece, August, 2017. PDF icon PDF Version (290.2 KB)
Scardapane, S., S. Van Vaerenbergh, D. Comminiello, S. Totaro, and A. Uncini, "Recurrent Neural Networks With Flexible Gates Using Kernel Activation Functions", IEEE International Workshop on Machine Learning for Signal Processing, Aalborg, Denmark, IEEE, September, 2018.
Fernández-Bes, J., V. Elvira, and S. Van Vaerenbergh, "A Probabilistic Least-Mean-Squares Filter", 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brisbane, Queensland, Australia, April, 2015. PDF icon PDF Version (375.31 KB)
Park, I M., S. Seth, and S. Van Vaerenbergh, "Probabilistic Kernel Least Mean Squares Algorithms", 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 05/2014. PDF icon PDF Version (383.6 KB)
Van Vaerenbergh, S., Ó. González, J. Vía, and I. Santamaría, "Physical Layer Authentication based on Channel Response Tracking using Gaussian Processes", 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 2429--2433, May, 2014. PDF icon PDF Version (376.13 KB)
Van Vaerenbergh, S., I. Santamaría, V. Elvira, and M. Salvatori, "Pattern Localization in Time Series through Signal-To-Model Alignment in Latent Space", 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Calgary, Alberta, Canada, IEEE, April, 2018. PDF icon PDF Version (262.96 KB)
Van Vaerenbergh, S., 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 icon PDF Version (286.89 KB)
Van Vaerenbergh, S., J. Vía, and I. Santamaría, "Online kernel canonical correlation analysis for supervised equalization of Wiener systems", IEEE International Joint Conference on Neural Networks (IJCNN 2006), Vancouver, Canada, July, 2006. PDF icon PDF Version (322.74 KB)
Pulgarin-Giraldo, J. Diego, A. Marino Alvarez-Meza, S. Van Vaerenbergh, I. Santamaría, and G. Castellanos, "MoCap multichannel time series representation and relevance analysis by kernel adaptive filtering and multikernel learning oriented to action recognition tasks", International Conference on Time Series and Forecasting (ITISE 2018), Granada, Spain, pp. 1316-1327, September, 2018. PDF icon PDF Version (417.25 KB)
Van Vaerenbergh, S., and L. A. Azpicueta-Ruiz, "Kernel-Based Identification of Hammerstein Systems for Nonlinear Acoustic Echo-Cancellation", 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 05/2014. PDF icon PDF Version (278.33 KB)
Van Vaerenbergh, S., 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, Cancun, Mexico, October, 2008. PDF icon PDF Version (136.65 KB)
Van Vaerenbergh, S., and I. Santamaría, "Kernel Adaptive Filtering: Which Technique to Choose in Practice", International Workshop on Advances in Regularization, Optimization, Kernel Methods and Support Vector Machines: theory and applications (ROKS 2013), pp. 101--102, July, 2013.
Scardapane, S., S. Van Vaerenbergh, D. Comminiello, and A. Uncini, "Improving Graph Convolutional Networks with Non-Parametric Activation Functions", 26th European Signal Processing Conference (EUSIPCO 2018), Rome, Italy, EURASIP, September, 2018.
Van Vaerenbergh, S., I. Santamaría, W. Liu, and J. C. Príncipe, "Fixed-Budget Kernel Recursive Least-Squares", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2010), Dallas, USA, March, 2010. PDF icon PDF Version (235.93 KB)
Manco-Vásquez, J., S. Van Vaerenbergh, J. Vía, and I. Santamaría, "Experimental Evaluation of a Cooperative Kernel-Based Approach for Robust Spectrum Sensing", 8th IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM), A Coruña, Spain, June, 2014. PDF icon PDF Version (393.28 KB)
Van Vaerenbergh, S., I. Santamaría, and M. Lázaro-Gredilla, "Estimation of the Forgetting Factor in Kernel Recursive Least Squares", 2012 IEEE International Workshop On Machine Learning For Signal Processing (MLSP), September, 2012. PDF icon PDF Version (241.23 KB)
Stamenkovic, Z., S. Randjić, I. Santamaría, D. Markovic, S. Van Vaerenbergh, and U. Pešović, "Decision Support System for Plan and Crop Treatment and Protection based on Wireless Sensor Networks", 41st International Spring Seminar on Electronics Technology (ISSE), Zlatibor, Serbia, May, 2018. PDF icon PDF Version (481.76 KB)
Van Vaerenbergh, S., and I. Santamaría, "A Comparative Study of Kernel Adaptive Filtering Algorithms", 2013 IEEE Digital Signal Processing (DSP) Workshop and IEEE Signal Processing Education (SPE): IEEE, August, 2013. PDF icon PDF Version (121.63 KB)
Lázaro-Gredilla, M., 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 icon PDF Version (238.14 KB)
Pulgarin-Giraldo, J. Diego, A. Marino Alvarez-Meza, S. Van Vaerenbergh, I. Santamaría, and G. Castellanos, "Analysis and classification of MoCap data by Hilbert space embedding-based distance and multikernel learning", The 23rd Iberoamerican Congress on Pattern Recognition, Madrid, Spain, November, 2018. PDF icon PDF Version (886.56 KB)
Ramírez, D., I. Santamaría, S. Van Vaerenbergh, and L. L. Scharf, "An alternating optimization algorithm for two-channel factor analysis with common and uncommon factors", 52nd Asilomar Conference on Signals, Systems and Computers, Pacific Grove (CA), USA, IEEE, October, 2018. PDF icon PDF Version (206.51 KB)
Van Vaerenbergh, S., J. Vía, J. Manco-Vásquez, and I. Santamaría, "Adaptive Kernel Canonical Correlation Analysis Algorithms for Maximum and Minimum Variance", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013), Vancouver, Canada, May, 2013. PDF icon PDF Version (90.87 KB)
Book Chapter
Van Vaerenbergh, S., and I. 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.), The Netherlands, Shaker Publishing, 2008. PDF icon PDF Version (2.88 MB)
Van Vaerenbergh, S., and I. Santamaría, "Online Regression with Kernels", Regularization, Optimization, Kernels, and Support Vector Machines, no. Machine Learning & Pattern Recognition Series, New York, Chapman and Hall/CRC, pp. 477-501, 2014. PDF icon PDF Version (298.16 KB)
Van Vaerenbergh, S., "Adaptive Kernel Learning for Signal Processing", Digital Signal Processing with Kernel Methods: Wiley, 2018. PDF icon PDF Version (687.57 KB)

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