Weakly supervised nonnegative matrix factorization for user-driven clustering
Data Mining and Knowledge Discovery, Volume 29, Issue 6, 2014.
Nonnegative matrix factorizationSemi-supervised clusteringUser-driven clusteringRegularization
Clustering high-dimensional data and making sense out of its result is a challenging problem. In this paper, we present a weakly supervised nonnegative matrix factorization (NMF) and its symmetric version that take into account various prior information via regularization in clustering applications. Unlike many other existing methods, the...More
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