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Steven Van Vaerenbergh
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- affiliation: University of Cantabria
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2020 – today
- 2024
- [j17]Adrián Pérez-Suay
, Valero Laparra
Learning About Student Performance From Moodle Logs in a Higher Education Context With Gaussian Processes. Rev. Iberoam. de Tecnol. del Aprendiz. 19: 169-175 (2024) - [j16]Jorge Blanco Prieto
A Data Mining Approach for Health Transport Demand. Mach. Learn. Knowl. Extr. 6(1): 78-97 (2024) - [c23]Ayesha Vermani, Matthew Dowling, Hyungju Jeon, Ian D. Jordan, Josue Nassar, Yves Bernaerts, Yuan Zhao, Steven Van Vaerenbergh, Il Memming Park:
Real-Time Machine Learning Strategies for a New Kind of Neuroscience Experiments. EUSIPCO 2024: 1127-1131 - 2023
- [j15]Adrián Pérez-Suay
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): 19-27 (2023) - 2021
- [i15]Steven Van Vaerenbergh, Adrián Pérez-Suay:
A Classification of Artificial Intelligence Systems for Mathematics Education. CoRR abs/2107.06015 (2021) - 2020
- [j14]Stephan Rhode, Steven Van Vaerenbergh
Power prediction for electric vehicles using online machine learning. Eng. Appl. Artif. Intell. 87 (2020) - [j13]Simone Scardapane
Complex-Valued Neural Networks With Nonparametric Activation Functions. IEEE Trans. Emerg. Top. Comput. Intell. 4(2): 140-150 (2020) - [j12]David Ramírez
Multi-Channel Factor Analysis With Common and Unique Factors. IEEE Trans. Signal Process. 68: 113-126 (2020)
2010 – 2019
- 2019
- [j11]Simone Scardapane
Kafnets: Kernel-based non-parametric activation functions for neural networks. Neural Networks 110: 19-32 (2019) - [c22]Simone Scardapane, Steven Van Vaerenbergh
Widely Linear Kernels for Complex-valued Kernel Activation Functions. ICASSP 2019: 8528-8532 - [i14]Simone Scardapane, Steven Van Vaerenbergh, Danilo Comminiello, Aurelio Uncini:
Widely Linear Kernels for Complex-Valued Kernel Activation Functions. CoRR abs/1902.02085 (2019) - [i13]Michele Cirillo, Simone Scardapane, Steven Van Vaerenbergh, Aurelio Uncini:
On the Stability and Generalization of Learning with Kernel Activation Functions. CoRR abs/1903.11990 (2019) - 2018
- [c21]David Ramírez
An alternating optimization algorithm for two-channel factor analysis with common and uncommon factors. ACSSC 2018: 1743-1747 - [c20]Juan Diego Pulgarin-Giraldo
Analysis and Classification of MoCap Data by Hilbert Space Embedding-Based Distance and Multikernel Learning. CIARP 2018: 186-193 - [c19]Simone Scardapane, Steven Van Vaerenbergh
Improving Graph Convolutional Networks with Non-Parametric Activation Functions. EUSIPCO 2018: 872-876 - [c18]Steven Van Vaerenbergh
Pattern Localization in Time Series Through Signal-To-Model Alignment in Latent Space. ICASSP 2018: 2711-2715 - [c17]Simone Scardapane, Steven Van Vaerenbergh
Recurrent Neural Networks with flexible Gates using Kernel activation Functions. MLSP 2018: 1-6 - [i12]Steven Van Vaerenbergh, Ignacio Santamaría, Victor Elvira, Matteo Salvatori:
Pattern Localization in Time Series through Signal-To-Model Alignment in Latent Space. CoRR abs/1802.05910 (2018) - [i11]Simone Scardapane, Steven Van Vaerenbergh, Amir Hussain, Aurelio Uncini:
Complex-valued Neural Networks with Non-parametric Activation Functions. CoRR abs/1802.08026 (2018) - [i10]Simone Scardapane, Steven Van Vaerenbergh, Danilo Comminiello, Aurelio Uncini:
Improving Graph Convolutional Networks with Non-Parametric Activation Functions. CoRR abs/1802.09405 (2018) - [i9]Simone Scardapane, Steven Van Vaerenbergh, Danilo Comminiello, Simone Totaro, Aurelio Uncini:
Recurrent Neural Networks with Flexible Gates using Kernel Activation Functions. CoRR abs/1807.04065 (2018) - 2017
- [j10]Julio Manco-Vásquez
Kernel canonical correlation analysis for robust cooperative spectrum sensing in cognitive radio networks. Trans. Emerg. Telecommun. Technol. 28(1) (2017) - [c16]Steven Van Vaerenbergh
Recursive multikernel filters exploiting nonlinear temporal structure. EUSIPCO 2017: 2674-2678 - [i8]Steven Van Vaerenbergh, Simone Scardapane, Ignacio Santamaría:
Recursive Multikernel Filters Exploiting Nonlinear Temporal Structure. CoRR abs/1706.03533 (2017) - [i7]Simone Scardapane, Steven Van Vaerenbergh, Aurelio Uncini:
Kafnets: kernel-based non-parametric activation functions for neural networks. CoRR abs/1707.04035 (2017) - 2016
- [c15]Steven Van Vaerenbergh
A split kernel adaptive filtering architecture for nonlinear acoustic echo cancellation. EUSIPCO 2016: 1768-1772 - [c14]Steven Van Vaerenbergh
On the relationship between online Gaussian process regression and kernel least mean squares algorithms. MLSP 2016: 1-6 - [i6]Steven Van Vaerenbergh, Jesus Fernandez-Bes, Víctor Elvira:
On the Relationship between Online Gaussian Process Regression and Kernel Least Mean Squares Algorithms. CoRR abs/1609.03164 (2016) - 2015
- [c13]Jesus Fernandez-Bes
A probabilistic least-mean-squares filter. ICASSP 2015: 2199-2203 - [i5]Jesus Fernandez-Bes, Víctor Elvira, Steven Van Vaerenbergh:
A Probabilistic Least-Mean-Squares Filter. CoRR abs/1501.06929 (2015) - 2014
- [j9]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): 1967-1979 (2014) - [c12]Steven Van Vaerenbergh
Physical layer authentication based on channel response tracking using Gaussian processes. ICASSP 2014: 2410-2414 - [c11]Steven Van Vaerenbergh
Kernel-based identification of Hammerstein systems for nonlinear acoustic echo-cancellation. ICASSP 2014: 3739-3743 - [c10]Il Memming Park
Probabilistic kernel least mean squares algorithms. ICASSP 2014: 8272-8276 - [c9]Julio Manco-Vásquez
Experimental evaluation of a cooperative kernel-based approach for robust spectrum sensing. SAM 2014: 349-352 - 2013
- [j8]Steven Van Vaerenbergh
Semi-supervised object recognition based on Connected Image Transformations. Expert Syst. Appl. 40(17): 7069-7079 (2013) - [j7]Fernando Pérez-Cruz
Gaussian Processes for Nonlinear Signal Processing: An Overview of Recent Advances. IEEE Signal Process. Mag. 30(4): 40-50 (2013) - [j6]Steven Van Vaerenbergh
Blind Identification of SIMO Wiener Systems Based on Kernel Canonical Correlation Analysis. IEEE Trans. Signal Process. 61(9): 2219-2230 (2013) - [c8]Steven Van Vaerenbergh
Adaptive kernel canonical correlation analysis algorithms for maximum and minimum variance. ICASSP 2013: 3587-3591 - [i4]Fernando Pérez-Cruz, Steven Van Vaerenbergh, Juan José Murillo-Fuentes, Miguel Lázaro-Gredilla, Ignacio Santamaría:
Gaussian Processes for Nonlinear Signal Processing. CoRR abs/1303.2823 (2013) - [i3]Steven Van Vaerenbergh, Javier Vía, Ignacio Santamaría:
Blind Identification of SIMO Wiener Systems based on Kernel Canonical Correlation Analysis. CoRR abs/1303.3525 (2013) - [i2]Il Memming Park, Sohan Seth, Steven Van Vaerenbergh:
Bayesian Extensions of Kernel Least Mean Squares. CoRR abs/1310.5347 (2013) - 2012
- [j5]Miguel Lázaro-Gredilla, Steven Van Vaerenbergh
Overlapping Mixtures of Gaussian Processes for the data association problem. Pattern Recognit. 45(4): 1386-1395 (2012) - [j4]Steven Van Vaerenbergh
Kernel Recursive Least-Squares Tracker for Time-Varying Regression. IEEE Trans. Neural Networks Learn. Syst. 23(8): 1313-1326 (2012) - [c7]Steven Van Vaerenbergh
Estimation of the forgetting factor in kernel recursive least squares. MLSP 2012: 1-6 - 2011
- [c6]Steven Van Vaerenbergh
Semi-supervised handwritten digit recognition using very few labeled data. ICASSP 2011: 2136-2139 - [c5]Miguel Lázaro-Gredilla, Steven Van Vaerenbergh
A Bayesian approach to tracking with kernel recursive least-squares. MLSP 2011: 1-6 - [i1]Miguel Lázaro-Gredilla, Steven Van Vaerenbergh, Neil D. Lawrence
Overlapping Mixtures of Gaussian Processes for the Data Association Problem. CoRR abs/1108.3372 (2011) - 2010
- [c4]Steven Van Vaerenbergh
Fixed-budget kernel recursive least-squares. ICASSP 2010: 1882-1885
2000 – 2009
- 2008
- [j3]Steven Van Vaerenbergh
Adaptive Kernel Canonical Correlation Analysis Algorithms for Nonparametric Identification of Wiener and Hammerstein Systems. EURASIP J. Adv. Signal Process. 2008 (2008) - 2007
- [j2]Steven Van Vaerenbergh
Nonlinear System Identification using a New Sliding-Window Kernel RLS Algorithm. J. Commun. 2(3): 1-8 (2007) - [c3]Steven Van Vaerenbergh, Emilio J. Estébanez, Ignacio Santamaría:
A spectral clustering algorithm for decoding fast time-varying BPSK mimo channels. EUSIPCO 2007: 479-483 - 2006
- [j1]Steven Van Vaerenbergh
A spectral clustering approach to underdetermined postnonlinear blind source separation of sparse sources. IEEE Trans. Neural Networks 17(3): 811-814 (2006) - [c2]Steven Van Vaerenbergh, Javier Vía, Ignacio Santamaría:
A Sliding-Window Kernel RLS Algorithm and Its Application to Nonlinear Channel Identification. ICASSP (5) 2006: 789-792 - [c1]Steven Van Vaerenbergh
Online Kernel Canonical Correlation Analysis for Supervised Equalization of Wiener Systems. IJCNN 2006: 1198-1204
Coauthor Index
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