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Context: Exploring the design space is an important process in a design task. In this study, we considered design space exploration for the learners in vocational education and training (VET). The goal of the study was to investigate how they explore the d ...
In social learning, agents form their opinions or beliefs about certain hypotheses by exchanging local information. This work considers the recent paradigm of weak graphs, where the network is partitioned into sending and receiving components, with the for ...
An abstract topological graph (briefly an AT-graph) is a pair A = (G, X) where G = (V, E) is a graph and X. E2 is a set of pairs of its edges. The AT-graph A is simply realizable if G can be drawn in the plane so that each pair of edges from X crosses exac ...
A graph is a versatile data structure facilitating representation of interactions among objects in various complex systems. Very often these objects have attributes whose measurements change over time, reflecting the dynamics of the system. This general da ...
Graph processing systems are used in a wide variety of fields, ranging from biology to social networks.
Algorithms to mine graphs incur many random accesses, and the sparse nature of the graphs of interest, exacerbates this. As DRAM sustains high bandwidt ...
Can one reduce the size of a graph without significantly altering its basic properties? The graph reduction problem is hereby approached from the perspective of restricted spectral approximation, a modification of the spectral similarity measure used for g ...
Understanding the origins of militarized conflict is a complex, yet important undertaking. Existing research seeks to build this understanding by considering bi-lateral relationships between entity pairs (dyadic causes) and multi-lateral relationships amon ...
Though deep learning (DL) algorithms are very powerful for image processing tasks, they generally require a lot of data to reach their full potential. Furthermore, there is no straightforward way to impose various properties, given by the prior knowledge a ...
The articles in this special section focus on graph signal processing. Generically, the networks that sustain our societies can be understood as complex systems formed by multiple nodes, where global network behavior arises from local interactions between ...
In several machine learning tasks for graph structured data, the graphs under consideration may be composed of a varying number of nodes. Therefore, it is necessary to design pooling methods that aggregate the graph representations of varying size to repre ...
