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A Classification of Artificial Intelligence Systems for Mathematics Education


Jul 13, 2021
Steven Van Vaerenbergh, Adrián Pérez-Suay

* Chapter in the upcoming book "Mathematics Education in the Age of Artificial Intelligence: How Artificial Intelligence can serve Mathematical Human Learning", Springer Nature, edited by P.R. Richard, P. V\'elez, and S. Van Vaerenbergh 

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On the Stability and Generalization of Learning with Kernel Activation Functions


Mar 28, 2019
Michele Cirillo, Simone Scardapane, Steven Van Vaerenbergh, Aurelio Uncini

* Submitted as a brief paper to IEEE TNNLS 

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Widely Linear Kernels for Complex-Valued Kernel Activation Functions


Feb 06, 2019
Simone Scardapane, Steven Van Vaerenbergh, Danilo Comminiello, Aurelio Uncini

* Accepted at ICASSP 2019 

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Recurrent Neural Networks with Flexible Gates using Kernel Activation Functions


Jul 11, 2018
Simone Scardapane, Steven Van Vaerenbergh, Danilo Comminiello, Simone Totaro, Aurelio Uncini

* Accepted for presentation at 2018 IEEE International Workshop on Machine Learning for Signal Processing (MLSP) 

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Improving Graph Convolutional Networks with Non-Parametric Activation Functions


Feb 26, 2018
Simone Scardapane, Steven Van Vaerenbergh, Danilo Comminiello, Aurelio Uncini

* Submitted to EUSIPCO 2018 

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Complex-valued Neural Networks with Non-parametric Activation Functions


Feb 22, 2018
Simone Scardapane, Steven Van Vaerenbergh, Amir Hussain, Aurelio Uncini

* Submitted to IEEE Transactions on Emerging Topics in Computational Intelligence 

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Pattern Localization in Time Series through Signal-To-Model Alignment in Latent Space


Feb 19, 2018
Steven Van Vaerenbergh, Ignacio Santamaria, Victor Elvira, Matteo Salvatori

* IEEE ICASSP 2018 

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Kafnets: kernel-based non-parametric activation functions for neural networks


Nov 23, 2017
Simone Scardapane, Steven Van Vaerenbergh, Simone Totaro, Aurelio Uncini

* Preprint submitted to Neural Networks (Elsevier) 

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Recursive Multikernel Filters Exploiting Nonlinear Temporal Structure


Jun 12, 2017
Steven Van Vaerenbergh, Simone Scardapane, Ignacio Santamaria

* Eusipco 2017 

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On the Relationship between Online Gaussian Process Regression and Kernel Least Mean Squares Algorithms


Sep 11, 2016
Steven Van Vaerenbergh, Jesus Fernandez-Bes, VĂ­ctor Elvira

* Accepted for publication in 2016 IEEE International Workshop on Machine Learning for Signal Processing 

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A Probabilistic Least-Mean-Squares Filter


Jan 27, 2015
Jesus Fernandez-Bes, VĂ­ctor Elvira, Steven Van Vaerenbergh


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Bayesian Extensions of Kernel Least Mean Squares


Oct 20, 2013
Il Memming Park, Sohan Seth, Steven Van Vaerenbergh

* 7 pages, 4 fiures 

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Gaussian Processes for Nonlinear Signal Processing


Sep 27, 2013
Fernando Pérez-Cruz, Steven Van Vaerenbergh, Juan José Murillo-Fuentes, Miguel Lázaro-Gredilla, Ignacio Santamaria

* IEEE Signal Processing Magazine, vol.30, no.4, pp.40-50, July 2013 

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Overlapping Mixtures of Gaussian Processes for the Data Association Problem


Aug 16, 2011
Miguel Lázaro-Gredilla, Steven Van Vaerenbergh, Neil Lawrence


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