Titlebook: Structural, Syntactic, and Statistical Pattern Recognition; Joint IAPR Internati Andrea Torsello,Luca Rossi,Antonio Robles-Kelly Conference

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Complex-Valued Embeddings of Generic Proximity Datamilarity measure, which may not obey particular mathematical properties. This renders many machine learning methods invalid, leading to convergence problems and the loss of generalization behavior. In many cases, the preferred dissimilarity measure is not metric. If the input data are non-vectorial,

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Augmenting Graph Convolutional Neural Networks with Highpass Filters for the convolutional layer and consider the case of directed graphs. This allows for graph spectral theory and the connections between eigenfunctions over the graph and Fourier analysis to employ graph signal processing to obtain an architecture that “concatenates” low and high-pass filters to pro

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Selecting Features from Time Series Using Attention-Based Recurrent Neural Networksemely large amounts of such data are being generated every second. In this paper, we introduce the recurrent neural networks equipped with attention modules that quantify the importance of features, hence can be employed to select only an informative subset of all available features. Additionally, o