Recent trends in learning of structured and non-standard data

In many application domains data are not given in a classical vector space but occur in form of structural, sequential, relational charac- teristics or other non-standard formats. These data are often represented as graphs or by means of proximity matrices. Often these data sets are also huge and mathematically complicated to treat requesting for new ecient analysis algorithms which are the focus of this tutorial.

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