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Found 3 papers, 1 papers with code
Open-world Semi-supervised Novel Class Discovery
Traditional semi-supervised learning tasks assume that both labeled and unlabeled data follow the same class distribution, but the realistic open-world scenarios are of more complexity with unknown novel classes mixed in the unlabeled set.
Revisiting Representation Degeneration Problem in Language Modeling
They call it the representation degeneration problem and propose a cosine regularization to solve it.
Graph Clustering with Density-Cut
We demonstrate that our method has several attractive benefits: (a) Dcut provides an intuitive criterion to evaluate the goodness of a graph clustering in a more natural and precise way; (b) Built upon the density-connected tree, Dcut allows identifying the meaningful graph clusters of densely connected vertices efficiently; (c) The density-connected tree provides a connectivity map of vertices in a graph from a local density perspective.
Social and Information Networks Physics and Society
