Steven Van Vaerenbergh

58 papers B 1C 1Misc 10Journal 35Unranked 11
YearRankTypeTitle / Venue / Authors
2026 J jnl
On Learning the Arithmetic Mean in Fourth-Year Secondary Education Using Eye-Tracking: A Pilot Study.
Rev. Iberoam. de Tecnol. del Aprendiz.
Júlia Vicens Figueres, Adrián Pérez-Suay, Ana Belen Pascual Venteo, Steven Van Vaerenbergh, Ismael García-Bayona
2025 J jnl
Design and Validation of Guidelines for Creating Mathematical Applets for Students With Autism.
Rev. Iberoam. de Tecnol. del Aprendiz.
Steven Van Vaerenbergh, Irene Polo-Blanco, Álvaro García Gómez
2025 J jnl
Exploring the Influence of Visual Aids in Mathematical Problem Solving: An Eye-Tracking Study With Prospective Teachers.
IEEE Trans. Educ.
Ismael García-Bayona, Adrián Pérez-Suay, Steven Van Vaerenbergh, Ana Belen Pascual Venteo
2024 J jnl
A Data Mining Approach for Health Transport Demand.
Mach. Learn. Knowl. Extr.
Jorge Blanco Prieto, Marina Ferreras González, Steven Van Vaerenbergh, Oscar Jesús Cosido Cobos
2024 J jnl
Learning About Student Performance From Moodle Logs in a Higher Education Context With Gaussian Processes.
Rev. Iberoam. de Tecnol. del Aprendiz.
Adrián Pérez-Suay, Valero Laparra, Steven Van Vaerenbergh, Ana Belen Pascual Venteo
2024 — conf
Real-Time Machine Learning Strategies for a New Kind of Neuroscience Experiments.
EUSIPCO
Ayesha Vermani, Matthew Dowling, Hyungju Jeon, Ian D. Jordan, Josue Nassar, Yves Bernaerts, Yuan Zhao, Steven Van Vaerenbergh, Il Memming Park
2023 J jnl
Data-Driven Modeling Through the Moodle Learning Management System: An Empirical Study Based on a Mathematics Teaching Subject.
Rev. Iberoam. de Tecnol. del Aprendiz.
Adrián Pérez-Suay, Steven Van Vaerenbergh, Pascual D. Diago, Ana Belen Pascual Venteo, Francesc J. Ferri
2021 J jnl
A Classification of Artificial Intelligence Systems for Mathematics Education.
CoRR
Steven Van Vaerenbergh, Adrián Pérez-Suay
2020 J jnl
Complex-Valued Neural Networks With Nonparametric Activation Functions.
IEEE Trans. Emerg. Top. Comput. Intell.
Simone Scardapane, Steven Van Vaerenbergh, Amir Hussain, Aurelio Uncini
2020 J jnl
Multi-Channel Factor Analysis With Common and Unique Factors.
IEEE Trans. Signal Process.
David Ramírez, Ignacio Santamaría, Louis L. Scharf, Steven Van Vaerenbergh
2020 J jnl
Power prediction for electric vehicles using online machine learning.
Eng. Appl. Artif. Intell.
Stephan Rhode, Steven Van Vaerenbergh, Matthias Pfriem
2019 J jnl
Kafnets: Kernel-based non-parametric activation functions for neural networks.
Neural Networks
Simone Scardapane, Steven Van Vaerenbergh, Simone Totaro, Aurelio Uncini
2019 J jnl
On the Stability and Generalization of Learning with Kernel Activation Functions.
CoRR
Michele Cirillo, Simone Scardapane, Steven Van Vaerenbergh, Aurelio Uncini
2019 J jnl
Widely Linear Kernels for Complex-Valued Kernel Activation Functions.
CoRR
Simone Scardapane, Steven Van Vaerenbergh, Danilo Comminiello, Aurelio Uncini
2019 Misc conf
Widely Linear Kernels for Complex-valued Kernel Activation Functions.
ICASSP
Simone Scardapane, Steven Van Vaerenbergh, Danilo Comminiello, Aurelio Uncini
2018 Misc conf
An alternating optimization algorithm for two-channel factor analysis with common and uncommon factors.
ACSSC
David Ramírez, Ignacio Santamaría, Steven Van Vaerenbergh, Louis L. Scharf
2018 C conf
Analysis and Classification of MoCap Data by Hilbert Space Embedding-Based Distance and Multikernel Learning.
CIARP
Juan Diego Pulgarin-Giraldo, Andrés Marino Álvarez-Meza, Steven Van Vaerenbergh, Ignacio Santamaría, Germán Castellanos-Domínguez
2018 J jnl
Complex-valued Neural Networks with Non-parametric Activation Functions.
CoRR
Simone Scardapane, Steven Van Vaerenbergh, Amir Hussain, Aurelio Uncini
2018 — conf
Improving Graph Convolutional Networks with Non-Parametric Activation Functions.
EUSIPCO
Simone Scardapane, Steven Van Vaerenbergh, Danilo Comminiello, Aurelio Uncini
2018 J jnl
Improving Graph Convolutional Networks with Non-Parametric Activation Functions.
CoRR
Simone Scardapane, Steven Van Vaerenbergh, Danilo Comminiello, Aurelio Uncini
2018 Misc conf
Pattern Localization in Time Series Through Signal-To-Model Alignment in Latent Space.
ICASSP
Steven Van Vaerenbergh, Ignacio Santamaría, Victor Elvira, Matteo Salvatori
2018 J jnl
Pattern Localization in Time Series through Signal-To-Model Alignment in Latent Space.
CoRR
Steven Van Vaerenbergh, Ignacio Santamaría, Victor Elvira, Matteo Salvatori
2018 J jnl
Recurrent Neural Networks with Flexible Gates using Kernel Activation Functions.
CoRR
Simone Scardapane, Steven Van Vaerenbergh, Danilo Comminiello, Simone Totaro, Aurelio Uncini
2018 — conf
Recurrent Neural Networks with flexible Gates using Kernel activation Functions.
MLSP
Simone Scardapane, Steven Van Vaerenbergh, Danilo Comminiello, Simone Totaro, Aurelio Uncini
2017 J jnl
Kafnets: kernel-based non-parametric activation functions for neural networks.
CoRR
Simone Scardapane, Steven Van Vaerenbergh, Aurelio Uncini
2017 J jnl
Kernel canonical correlation analysis for robust cooperative spectrum sensing in cognitive radio networks.
Trans. Emerg. Telecommun. Technol.
Julio Manco-Vásquez, Steven Van Vaerenbergh, Javier Vía Rodríguez, Ignacio Santamaría
2017 J jnl
Recursive Multikernel Filters Exploiting Nonlinear Temporal Structure.
CoRR
Steven Van Vaerenbergh, Simone Scardapane, Ignacio Santamaría
2017 — conf
Recursive multikernel filters exploiting nonlinear temporal structure.
EUSIPCO
Steven Van Vaerenbergh, Simone Scardapane, Ignacio Santamaría
2016 — conf
A split kernel adaptive filtering architecture for nonlinear acoustic echo cancellation.
EUSIPCO
Steven Van Vaerenbergh, Luis Antonio Azpicueta-Ruiz, Danilo Comminiello
2016 J jnl
On the Relationship between Online Gaussian Process Regression and Kernel Least Mean Squares Algorithms.
CoRR
Steven Van Vaerenbergh, Jesus Fernandez-Bes, Víctor Elvira
2016 — conf
On the relationship between online Gaussian process regression and kernel least mean squares algorithms.
MLSP
Steven Van Vaerenbergh, Jesus Fernandez-Bes, Victor Elvira
2015 J jnl
A Probabilistic Least-Mean-Squares Filter.
CoRR
Jesus Fernandez-Bes, Víctor Elvira, Steven Van Vaerenbergh
2015 Misc conf
A probabilistic least-mean-squares filter.
ICASSP
Jesus Fernandez-Bes, Víctor Elvira, Steven Van Vaerenbergh
2014 J jnl
A Gaussian Process Model for Data Association and a Semidefinite Programming Solution.
IEEE Trans. Neural Networks Learn. Syst.
Miguel Lázaro-Gredilla, Steven Van Vaerenbergh
2014 — conf
Experimental evaluation of a cooperative kernel-based approach for robust spectrum sensing.
SAM
Julio Manco-Vásquez, Steven Van Vaerenbergh, Javier Vía, Ignacio Santamaría
2014 Misc conf
Kernel-based identification of Hammerstein systems for nonlinear acoustic echo-cancellation.
ICASSP
Steven Van Vaerenbergh, Luis Antonio Azpicueta-Ruiz
2014 Misc conf
Physical layer authentication based on channel response tracking using Gaussian processes.
ICASSP
Steven Van Vaerenbergh, Oscar Gonzalez, Javier Vía, Ignacio Santamaría
2014 Misc conf
Probabilistic kernel least mean squares algorithms.
ICASSP
Il Memming Park, Sohan Seth, Steven Van Vaerenbergh
2013 Misc conf
Adaptive kernel canonical correlation analysis algorithms for maximum and minimum variance.
ICASSP
Steven Van Vaerenbergh, Javier Vía, Julio Manco-Vásquez, Ignacio Santamaría
2013 J jnl
Bayesian Extensions of Kernel Least Mean Squares.
CoRR
Il Memming Park, Sohan Seth, Steven Van Vaerenbergh
2013 J jnl
Blind Identification of SIMO Wiener Systems Based on Kernel Canonical Correlation Analysis.
IEEE Trans. Signal Process.
Steven Van Vaerenbergh, Javier Vía, Ignacio Santamaría
2013 J jnl
Blind Identification of SIMO Wiener Systems based on Kernel Canonical Correlation Analysis
CoRR
Steven Van Vaerenbergh, Javier Vía, Ignacio Santamaría
2013 J jnl
Gaussian Processes for Nonlinear Signal Processing
CoRR
Fernando Pérez-Cruz, Steven Van Vaerenbergh, Juan José Murillo-Fuentes, Miguel Lázaro-Gredilla, Ignacio Santamaría
2013 J jnl
Gaussian Processes for Nonlinear Signal Processing: An Overview of Recent Advances.
IEEE Signal Process. Mag.
Fernando Pérez-Cruz, Steven Van Vaerenbergh, Juan José Murillo-Fuentes, Miguel Lázaro-Gredilla, Ignacio Santamaría
2013 J jnl
Semi-supervised object recognition based on Connected Image Transformations.
Expert Syst. Appl.
Steven Van Vaerenbergh, Ignacio Santamaría, Paolo Emilio Barbano
2012 — conf
Estimation of the forgetting factor in kernel recursive least squares.
MLSP
Steven Van Vaerenbergh, Ignacio Santamaría, Miguel Lázaro-Gredilla
2012 J jnl
Kernel Recursive Least-Squares Tracker for Time-Varying Regression.
IEEE Trans. Neural Networks Learn. Syst.
Steven Van Vaerenbergh, Miguel Lázaro-Gredilla, Ignacio Santamaría
2012 J jnl
Overlapping Mixtures of Gaussian Processes for the data association problem.
Pattern Recognit.
Miguel Lázaro-Gredilla, Steven Van Vaerenbergh, Neil D. Lawrence
2011 — conf
A Bayesian approach to tracking with kernel recursive least-squares.
MLSP
Miguel Lázaro-Gredilla, Steven Van Vaerenbergh, Ignacio Santamaría
2011 J jnl
Overlapping Mixtures of Gaussian Processes for the Data Association Problem
CoRR
Miguel Lázaro-Gredilla, Steven Van Vaerenbergh, Neil D. Lawrence
2011 Misc conf
Semi-supervised handwritten digit recognition using very few labeled data.
ICASSP
Steven Van Vaerenbergh, Ignacio Santamaría, Paolo Emilio Barbano
2010 Misc conf
Fixed-budget kernel recursive least-squares.
ICASSP
Steven Van Vaerenbergh, Ignacio Santamaría, Weifeng Liu, José C. Príncipe
2008 J jnl
Adaptive Kernel Canonical Correlation Analysis Algorithms for Nonparametric Identification of Wiener and Hammerstein Systems.
EURASIP J. Adv. Signal Process.
Steven Van Vaerenbergh, Javier Vía, Ignacio Santamaría
2007 — conf
A spectral clustering algorithm for decoding fast time-varying BPSK mimo channels.
EUSIPCO
Steven Van Vaerenbergh, Emilio J. Estébanez, Ignacio Santamaría
2007 J jnl
Nonlinear System Identification using a New Sliding-Window Kernel RLS Algorithm.
J. Commun.
Steven Van Vaerenbergh, Javier Vía, Ignacio Santamaría
2006 — conf
A Sliding-Window Kernel RLS Algorithm and Its Application to Nonlinear Channel Identification.
ICASSP (5)
Steven Van Vaerenbergh, Javier Vía, Ignacio Santamaría
2006 J jnl
A spectral clustering approach to underdetermined postnonlinear blind source separation of sparse sources.
IEEE Trans. Neural Networks
Steven Van Vaerenbergh, Ignacio Santamaría
2006 B conf
Online Kernel Canonical Correlation Analysis for Supervised Equalization of Wiener Systems.
IJCNN
Steven Van Vaerenbergh, Javier Vía, Ignacio Santamaría