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07/13/2021
A Classification of Artificial Intelligence Systems for Mathematics Education
This chapter provides an overview of the different Artificial Intelligen...
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03/28/2019
On the Stability and Generalization of Learning with Kernel Activation Functions
In this brief we investigate the generalization properties of a recently...
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02/06/2019
Widely Linear Kernels for Complex-Valued Kernel Activation Functions
Complex-valued neural networks (CVNNs) have been shown to be powerful no...
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07/11/2018
Recurrent Neural Networks with Flexible Gates using Kernel Activation Functions
Gated recurrent neural networks have achieved remarkable results in the ...
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02/26/2018
Improving Graph Convolutional Networks with Non-Parametric Activation Functions
Graph neural networks (GNNs) are a class of neural networks that allow t...
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02/22/2018
Complex-valued Neural Networks with Non-parametric Activation Functions
Complex-valued neural networks (CVNNs) are a powerful modeling tool for ...
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02/16/2018
Pattern Localization in Time Series through Signal-To-Model Alignment in Latent Space
In this paper, we study the problem of locating a predefined sequence of...
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07/13/2017
Kafnets: kernel-based non-parametric activation functions for neural networks
Neural networks are generally built by interleaving (adaptable) linear l...
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06/12/2017
Recursive Multikernel Filters Exploiting Nonlinear Temporal Structure
In kernel methods, temporal information on the data is commonly included...
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09/11/2016
On the Relationship between Online Gaussian Process Regression and Kernel Least Mean Squares Algorithms
We study the relationship between online Gaussian process (GP) regressio...
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01/27/2015
A Probabilistic Least-Mean-Squares Filter
We introduce a probabilistic approach to the LMS filter. By means of an ...
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03/12/2013
Gaussian Processes for Nonlinear Signal Processing
Gaussian processes (GPs) are versatile tools that have been successfully...
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08/16/2011
