A Sliding-Window Kernel RLS Algorithm and Its Application to Nonlinear Channel Identification. - Steven Van Vaerenbergh; Javier Vía; Ignacio Santamaría (ICASSP (5), 2006)

Online Kernel Canonical Correlation Analysis for Supervised Equalization of Wiener Systems. - Steven Van Vaerenbergh; Javier Vía; Ignacio Santamaría (IJCNN, 2006)

A spectral clustering approach to underdetermined postnonlinear blind source separation of sparse sources. - Steven Van Vaerenbergh; Ignacio Santamaría (IEEE Trans. Neural Networks, 2006)

A spectral clustering algorithm for decoding fast time-varying BPSK mimo channels. - Steven Van Vaerenbergh; Emilio J. Estébanez; Ignacio Santamaría (EUSIPCO, 2007)

Nonlinear System Identification using a New Sliding-Window Kernel RLS Algorithm. - Steven Van Vaerenbergh; Javier Vía; Ignacio Santamaría (J. Commun., 2007)

Adaptive Kernel Canonical Correlation Analysis Algorithms for Nonparametric Identification of Wiener and Hammerstein Systems. - Steven Van Vaerenbergh; Javier Vía; Ignacio Santamaría (EURASIP J. Adv. Signal Process., 2008)

Fixed-budget kernel recursive least-squares. - Steven Van Vaerenbergh; Ignacio Santamaría; Weifeng Liu 001; José C. Príncipe (ICASSP, 2010)

Semi-supervised handwritten digit recognition using very few labeled data. - Steven Van Vaerenbergh; Ignacio Santamaría; Paolo Emilio Barbano (ICASSP, 2011)

A Bayesian approach to tracking with kernel recursive least-squares. - Miguel Lázaro-Gredilla; Steven Van Vaerenbergh; Ignacio Santamaría (MLSP, 2011)

Estimation of the forgetting factor in kernel recursive least squares. - Steven Van Vaerenbergh; Ignacio Santamaría; Miguel Lázaro-Gredilla (MLSP, 2012)

Overlapping Mixtures of Gaussian Processes for the data association problem. - Miguel Lázaro-Gredilla; Steven Van Vaerenbergh; Neil D. Lawrence (Pattern Recognit., 2012)

Kernel Recursive Least-Squares Tracker for Time-Varying Regression. - Steven Van Vaerenbergh; Miguel Lázaro-Gredilla; Ignacio Santamaría (IEEE Trans. Neural Networks Learn. Syst., 2012)

Adaptive kernel canonical correlation analysis algorithms for maximum and minimum variance. - Steven Van Vaerenbergh; Javier Vía; Julio Manco-Vásquez; Ignacio Santamaría (ICASSP, 2013)

Bayesian Extensions of Kernel Least Mean Squares. - Il Memming Park; Sohan Seth; Steven Van Vaerenbergh (CoRR, 2013)

Gaussian Processes for Nonlinear Signal Processing - Fernando Pérez-Cruz; Steven Van Vaerenbergh; Juan José Murillo-Fuentes; Miguel Lázaro-Gredilla; Ignacio Santamaría (CoRR, 2013)

Semi-supervised object recognition based on Connected Image Transformations. - Steven Van Vaerenbergh; Ignacio Santamaría; Paolo Emilio Barbano (Expert Syst. Appl., 2013)

Gaussian Processes for Nonlinear Signal Processing: An Overview of Recent Advances. - Fernando Pérez-Cruz; Steven Van Vaerenbergh; Juan José Murillo-Fuentes; Miguel Lázaro-Gredilla; Ignacio Santamaría (IEEE Signal Process. Mag., 2013)

Blind Identification of SIMO Wiener Systems Based on Kernel Canonical Correlation Analysis. - Steven Van Vaerenbergh; Javier Vía; Ignacio Santamaría (IEEE Trans. Signal Process., 2013)

Probabilistic kernel least mean squares algorithms. - Il Memming Park; Sohan Seth; Steven Van Vaerenbergh (ICASSP, 2014)

Kernel-based identification of Hammerstein systems for nonlinear acoustic echo-cancellation. - Steven Van Vaerenbergh; Luis Antonio Azpicueta-Ruiz (ICASSP, 2014)

Physical layer authentication based on channel response tracking using Gaussian processes. - Steven Van Vaerenbergh; Oscar Gonzalez; Javier Vía; Ignacio Santamaría (ICASSP, 2014)

Experimental evaluation of a cooperative kernel-based approach for robust spectrum sensing. - Julio Manco-Vásquez; Steven Van Vaerenbergh; Javier Vía; Ignacio Santamaría (SAM, 2014)

A Gaussian Process Model for Data Association and a Semidefinite Programming Solution. - Miguel Lázaro-Gredilla; Steven Van Vaerenbergh (IEEE Trans. Neural Networks Learn. Syst., 2014)

A probabilistic least-mean-squares filter. - Jesus Fernandez-Bes; Víctor Elvira; Steven Van Vaerenbergh (ICASSP, 2015)

A split kernel adaptive filtering architecture for nonlinear acoustic echo cancellation. - Steven Van Vaerenbergh; Luis Antonio Azpicueta-Ruiz; Danilo Comminiello (EUSIPCO, 2016)

On the relationship between online Gaussian process regression and kernel least mean squares algorithms. - Steven Van Vaerenbergh; Jesus Fernandez-Bes; Victor Elvira (MLSP, 2016)

Recursive multikernel filters exploiting nonlinear temporal structure. - Steven Van Vaerenbergh; Simone Scardapane; Ignacio Santamaría (EUSIPCO, 2017)

Kafnets: kernel-based non-parametric activation functions for neural networks. - Simone Scardapane; Steven Van Vaerenbergh; Aurelio Uncini (CoRR, 2017)

Kernel canonical correlation analysis for robust cooperative spectrum sensing in cognitive radio networks. - Julio Manco-Vásquez; Steven Van Vaerenbergh; Javier Vía Rodríguez; Ignacio Santamaría (Trans. Emerg. Telecommun. Technol., 2017)

An alternating optimization algorithm for two-channel factor analysis with common and uncommon factors. - David Ramírez 001; Ignacio Santamaría; Steven Van Vaerenbergh; Louis L. Scharf (ACSSC, 2018)

Analysis and Classification of MoCap Data by Hilbert Space Embedding-Based Distance and Multikernel Learning. - Juan Diego Pulgarin-Giraldo; Andrés Marino Álvarez-Meza; Steven Van Vaerenbergh; Ignacio Santamaría; Germán Castellanos-Domínguez (CIARP, 2018)

Improving Graph Convolutional Networks with Non-Parametric Activation Functions. - Simone Scardapane; Steven Van Vaerenbergh; Danilo Comminiello; Aurelio Uncini (EUSIPCO, 2018)

Pattern Localization in Time Series Through Signal-To-Model Alignment in Latent Space. - Steven Van Vaerenbergh; Ignacio Santamaría; Victor Elvira; Matteo Salvatori (ICASSP, 2018)

Recurrent Neural Networks with flexible Gates using Kernel activation Functions. - Simone Scardapane; Steven Van Vaerenbergh; Danilo Comminiello; Simone Totaro; Aurelio Uncini (MLSP, 2018)

Complex-valued Neural Networks with Non-parametric Activation Functions. - Simone Scardapane; Steven Van Vaerenbergh; Amir Hussain 001; Aurelio Uncini (CoRR, 2018)

Widely Linear Kernels for Complex-valued Kernel Activation Functions. - Simone Scardapane; Steven Van Vaerenbergh; Danilo Comminiello; Aurelio Uncini (ICASSP, 2019)

On the Stability and Generalization of Learning with Kernel Activation Functions. - Michele Cirillo; Simone Scardapane; Steven Van Vaerenbergh; Aurelio Uncini (CoRR, 2019)

Kafnets: Kernel-based non-parametric activation functions for neural networks. - Simone Scardapane; Steven Van Vaerenbergh; Simone Totaro; Aurelio Uncini (Neural Networks, 2019)

Power prediction for electric vehicles using online machine learning. - Stephan Rhode; Steven Van Vaerenbergh; Matthias Pfriem (Eng. Appl. Artif. Intell., 2020)

Complex-Valued Neural Networks With Nonparametric Activation Functions. - Simone Scardapane; Steven Van Vaerenbergh; Amir Hussain 001; Aurelio Uncini (IEEE Trans. Emerg. Top. Comput. Intell., 2020)

Multi-Channel Factor Analysis With Common and Unique Factors. - David Ramírez 001; Ignacio Santamaría; Louis L. Scharf; Steven Van Vaerenbergh (IEEE Trans. Signal Process., 2020)

A Classification of Artificial Intelligence Systems for Mathematics Education. - Steven Van Vaerenbergh; Adrián Pérez-Suay (CoRR, 2021)

Data-Driven Modeling Through the Moodle Learning Management System: An Empirical Study Based on a Mathematics Teaching Subject. - Adrián Pérez-Suay; Steven Van Vaerenbergh; Pascual D. Diago; Ana Belen Pascual Venteo; Francesc J. Ferri (Rev. Iberoam. de Tecnol. del Aprendiz., 2023)

Real-Time Machine Learning Strategies for a New Kind of Neuroscience Experiments. - Ayesha Vermani; Matthew Dowling; Hyungju Jeon; Ian D. Jordan; Josue Nassar; Yves Bernaerts; Yuan Zhao 004; Steven Van Vaerenbergh; Il Memming Park (EUSIPCO, 2024)

Learning About Student Performance From Moodle Logs in a Higher Education Context With Gaussian Processes. - Adrián Pérez-Suay; Valero Laparra; Steven Van Vaerenbergh; Ana Belen Pascual Venteo (Rev. Iberoam. de Tecnol. del Aprendiz., 2024)

A Data Mining Approach for Health Transport Demand. - Jorge Blanco Prieto; Marina Ferreras González; Steven Van Vaerenbergh; Oscar Jesús Cosido Cobos (Mach. Learn. Knowl. Extr., 2024)