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Multi-label classification has attracted many attentions in various fields, such as text categorization and semantic image annotation. Aiming to classify an instance into multiple labels, various multi-label classification methods have been proposed. However, the existing methods typically build models in the identical feature (sub)space for all labels, possibly inconsistent with real-world problems...
Nonnegative Tensor Factorization (NTF) has become a popular tool for extracting informative patterns from tensor data. However, NTF has high computational cost both in space and in time, mostly in iterative calculation of the gradient. In this paper, we consider variable selection to reduce the cost, assuming sparsity of the factor matrices. In fact, it is known that the factor matrices are often...
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