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The recent developments of statistical learning focused on vector machines, which learn from examples that are described by vectors of features. However, there are many fields where structured data must be handled; therefore, it would be desirable to learn from examples described by graphs.Graph machines learn real numbers from graphs. Basically, for each graph, a separate learning machine is built,...
The present paper is a short survey of the development of numerical learning from structured data, an old problem that was first addressed by the end of the years 1980, and has recently undergone exciting developments, both from a theoretical point of view and for applications. Traditionally, numerical machine learning deals with unstructured data, in the form of vectors: neural networks, graphical...
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