Generalized Sparse Learning of Linear Models Over the Complete Subgraph Feature Set
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DOI: 10.1109/tpami.2016.2567399
Abstract: Supervised learning over graphs is an intrinsically difficult problem: simultaneous learning of relevant features from the complete subgraph feature set, in which enumerating all subgraph features occurring in given graphs is practically intractable due to… read more here.
Keywords: subgraph feature; sparse learning; generalized sparse; complete subgraph ... See more keywords