Steven Van Vaerenbergh

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 28

Top Topics

Adaptive Filter

Least Mean Square

Factor Analysis

Top Venues

Publications

Jorge Blanco Prieto, Marina Ferreras González, Steven Van Vaerenbergh, Oscar Jesús Cosido Cobos
A Data Mining Approach for Health Transport Demand. Mach. Learn. Knowl. Extr. 6 (1) (2024)
Adrián Pérez-Suay, Steven Van Vaerenbergh, Pascual D. Diago, Ana B. Pascual-Venteo, Francesc J. Ferri
Data-Driven Modeling Through the Moodle Learning Management System: An Empirical Study Based on a Mathematics Teaching Subject. Rev. Iberoam. de Tecnol. del Aprendiz. 18 (1) (2023)
Steven Van Vaerenbergh, Adrián Pérez-Suay
A Classification of Artificial Intelligence Systems for Mathematics Education. CoRR (2021)
Stephan Rhode, Steven Van Vaerenbergh, Matthias Pfriem
Power prediction for electric vehicles using online machine learning. Eng. Appl. Artif. Intell. 87 (2020)
Simone Scardapane, Steven Van Vaerenbergh, Amir Hussain, Aurelio Uncini
Complex-Valued Neural Networks With Nonparametric Activation Functions. IEEE Trans. Emerg. Top. Comput. Intell. 4 (2) (2020)
David Ramírez, Ignacio Santamaría, Louis L. Scharf, Steven Van Vaerenbergh
Multi-Channel Factor Analysis With Common and Unique Factors. IEEE Trans. Signal Process. 68 (2020)
Michele Cirillo, Simone Scardapane, Steven Van Vaerenbergh, Aurelio Uncini
On the Stability and Generalization of Learning with Kernel Activation Functions. CoRR (2019)
Simone Scardapane, Steven Van Vaerenbergh, Simone Totaro, Aurelio Uncini
Kafnets: Kernel-based non-parametric activation functions for neural networks. Neural Networks 110 (2019)
Simone Scardapane, Steven Van Vaerenbergh, Danilo Comminiello, Aurelio Uncini
Widely Linear Kernels for Complex-Valued Kernel Activation Functions. CoRR (2019)
Simone Scardapane, Steven Van Vaerenbergh, Danilo Comminiello, Aurelio Uncini
Widely Linear Kernels for Complex-valued Kernel Activation Functions. ICASSP (2019)
Juan Diego Pulgarin-Giraldo, Andrés Marino Álvarez-Meza, Steven Van Vaerenbergh, Ignacio Santamaría, Germán Castellanos-Domínguez
Analysis and Classification of MoCap Data by Hilbert Space Embedding-Based Distance and Multikernel Learning. CIARP (2018)
Simone Scardapane, Steven Van Vaerenbergh, Danilo Comminiello, Simone Totaro, Aurelio Uncini
Recurrent Neural Networks with Flexible Gates using Kernel Activation Functions. CoRR (2018)
David Ramírez, Ignacio Santamaría, Steven Van Vaerenbergh, Louis L. Scharf
An alternating optimization algorithm for two-channel factor analysis with common and uncommon factors. ACSSC (2018)
Steven Van Vaerenbergh, Ignacio Santamaría, Victor Elvira, Matteo Salvatori
Pattern Localization in Time Series Through Signal-To-Model Alignment in Latent Space. ICASSP (2018)
Steven Van Vaerenbergh, Ignacio Santamaría, Victor Elvira, Matteo Salvatori
Pattern Localization in Time Series through Signal-To-Model Alignment in Latent Space. CoRR (2018)
Simone Scardapane, Steven Van Vaerenbergh, Amir Hussain, Aurelio Uncini
Complex-valued Neural Networks with Non-parametric Activation Functions. CoRR (2018)
Simone Scardapane, Steven Van Vaerenbergh, Danilo Comminiello, Aurelio Uncini
Improving Graph Convolutional Networks with Non-Parametric Activation Functions. CoRR (2018)
Simone Scardapane, Steven Van Vaerenbergh, Danilo Comminiello, Aurelio Uncini
Improving Graph Convolutional Networks with Non-Parametric Activation Functions. EUSIPCO (2018)
Simone Scardapane, Steven Van Vaerenbergh, Danilo Comminiello, Simone Totaro, Aurelio Uncini
Recurrent Neural Networks with flexible Gates using Kernel activation Functions. MLSP (2018)
Steven Van Vaerenbergh, Simone Scardapane, Ignacio Santamaría
Recursive Multikernel Filters Exploiting Nonlinear Temporal Structure. CoRR (2017)
J. Manco-Vasquez, Steven Van Vaerenbergh, Javier Vía Rodríguez, Ignacio Santamaría
Kernel canonical correlation analysis for robust cooperative spectrum sensing in cognitive radio networks. Trans. Emerg. Telecommun. Technol. 28 (1) (2017)
Simone Scardapane, Steven Van Vaerenbergh, Aurelio Uncini
Kafnets: kernel-based non-parametric activation functions for neural networks. CoRR (2017)
Steven Van Vaerenbergh, Simone Scardapane, Ignacio Santamaría
Recursive multikernel filters exploiting nonlinear temporal structure. EUSIPCO (2017)
Steven Van Vaerenbergh, Luis Antonio Azpicueta-Ruiz, Danilo Comminiello
A split kernel adaptive filtering architecture for nonlinear acoustic echo cancellation. EUSIPCO (2016)
Steven Van Vaerenbergh, Jesus Fernandez-Bes, Victor Elvira
On the relationship between online Gaussian process regression and kernel least mean squares algorithms. MLSP (2016)
Steven Van Vaerenbergh, Jesus Fernandez-Bes, Víctor Elvira
On the Relationship between Online Gaussian Process Regression and Kernel Least Mean Squares Algorithms. CoRR (2016)
Jesus Fernandez-Bes, Víctor Elvira, Steven Van Vaerenbergh
A probabilistic least-mean-squares filter. ICASSP (2015)
Jesus Fernandez-Bes, Víctor Elvira, Steven Van Vaerenbergh
A Probabilistic Least-Mean-Squares Filter. CoRR (2015)
Steven Van Vaerenbergh, Oscar Gonzalez, Javier Vía, Ignacio Santamaría
Physical layer authentication based on channel response tracking using Gaussian processes. ICASSP (2014)
Steven Van Vaerenbergh, Luis Antonio Azpicueta-Ruiz
Kernel-based identification of Hammerstein systems for nonlinear acoustic echo-cancellation. ICASSP (2014)
Il Memming Park, Sohan Seth, Steven Van Vaerenbergh
Probabilistic kernel least mean squares algorithms. ICASSP (2014)
Miguel Lázaro-Gredilla, Steven Van Vaerenbergh
A Gaussian Process Model for Data Association and a Semidefinite Programming Solution. IEEE Trans. Neural Networks Learn. Syst. 25 (11) (2014)
J. Manco-Vasquez, Steven Van Vaerenbergh, Javier Vía, Ignacio Santamaría
Experimental evaluation of a cooperative kernel-based approach for robust spectrum sensing. SAM (2014)
Fernando Pérez-Cruz, Steven Van Vaerenbergh, Juan José Murillo-Fuentes, Miguel Lázaro-Gredilla, Ignacio Santamaría
Gaussian Processes for Nonlinear Signal Processing: An Overview of Recent Advances. IEEE Signal Process. Mag. 30 (4) (2013)
Il Memming Park, Sohan Seth, Steven Van Vaerenbergh
Bayesian Extensions of Kernel Least Mean Squares. CoRR (2013)
Steven Van Vaerenbergh, Ignacio Santamaría, Paolo Emilio Barbano
Semi-supervised object recognition based on Connected Image Transformations. Expert Syst. Appl. 40 (17) (2013)
Steven Van Vaerenbergh, Javier Vía, Ignacio Santamaría
Blind Identification of SIMO Wiener Systems Based on Kernel Canonical Correlation Analysis. IEEE Trans. Signal Process. 61 (9) (2013)
Steven Van Vaerenbergh, Javier Vía, Ignacio Santamaría
Blind Identification of SIMO Wiener Systems based on Kernel Canonical Correlation Analysis CoRR (2013)
Steven Van Vaerenbergh, Javier Vía, J. Manco-Vasquez, Ignacio Santamaría
Adaptive kernel canonical correlation analysis algorithms for maximum and minimum variance. ICASSP (2013)
Fernando Pérez-Cruz, Steven Van Vaerenbergh, Juan José Murillo-Fuentes, Miguel Lázaro-Gredilla, Ignacio Santamaría
Gaussian Processes for Nonlinear Signal Processing CoRR (2013)
Miguel Lázaro-Gredilla, Steven Van Vaerenbergh, Neil D. Lawrence
Overlapping Mixtures of Gaussian Processes for the data association problem. Pattern Recognit. 45 (4) (2012)
Steven Van Vaerenbergh, Miguel Lázaro-Gredilla, Ignacio Santamaría
Kernel Recursive Least-Squares Tracker for Time-Varying Regression. IEEE Trans. Neural Networks Learn. Syst. 23 (8) (2012)
Steven Van Vaerenbergh, Ignacio Santamaría, Miguel Lázaro-Gredilla
Estimation of the forgetting factor in kernel recursive least squares. MLSP (2012)
Miguel Lázaro-Gredilla, Steven Van Vaerenbergh, Ignacio Santamaría
A Bayesian approach to tracking with kernel recursive least-squares. MLSP (2011)
Steven Van Vaerenbergh, Ignacio Santamaría, Paolo Emilio Barbano
Semi-supervised handwritten digit recognition using very few labeled data. ICASSP (2011)
Miguel Lázaro-Gredilla, Steven Van Vaerenbergh, Neil D. Lawrence
Overlapping Mixtures of Gaussian Processes for the Data Association Problem CoRR (2011)
Steven Van Vaerenbergh, Ignacio Santamaría, Weifeng Liu, José C. Príncipe
Fixed-budget kernel recursive least-squares. ICASSP (2010)
Steven Van Vaerenbergh, Javier Vía, Ignacio Santamaría
Adaptive Kernel Canonical Correlation Analysis Algorithms for Nonparametric Identification of Wiener and Hammerstein Systems. EURASIP J. Adv. Signal Process. 2008 (2008)
Steven Van Vaerenbergh, Emilio J. Estébanez, Ignacio Santamaría
A spectral clustering algorithm for decoding fast time-varying BPSK mimo channels. EUSIPCO (2007)
Steven Van Vaerenbergh, Javier Vía, Ignacio Santamaría
Nonlinear System Identification using a New Sliding-Window Kernel RLS Algorithm. J. Commun. 2 (3) (2007)
Steven Van Vaerenbergh, Javier Vía, Ignacio Santamaría
A Sliding-Window Kernel RLS Algorithm and Its Application to Nonlinear Channel Identification. ICASSP (5) (2006)
Steven Van Vaerenbergh, Ignacio Santamaría
A spectral clustering approach to underdetermined postnonlinear blind source separation of sparse sources. IEEE Trans. Neural Networks 17 (3) (2006)
Steven Van Vaerenbergh, Javier Vía, Ignacio Santamaría
Online Kernel Canonical Correlation Analysis for Supervised Equalization of Wiener Systems. IJCNN (2006)