Abstract: We introduce a distributed optimization framework for directed graph networks that addresses composite objective functions with smooth local components and a shared convex regulariser. Our ...
Abstract: Partial multi-label learning (PML) tackles the problem of learning from ambiguously annotated data, where instances are associated with candidate label sets containing both relevant and ...
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