Web: http://arxiv.org/abs/2201.03869

Jan. 12, 2022, 2:10 a.m. | Paul Irofti, Cristian Rusu, Andrei Pătraşcu

cs.LG updates on arXiv.org arxiv.org

Many applications like audio and image processing show that sparse
representations are a powerful and efficient signal modeling technique. Finding
an optimal dictionary that generates at the same time the sparsest
representations of data and the smallest approximation error is a hard problem
approached by dictionary learning (DL). We study how DL performs in detecting
abnormal samples in a dataset of signals. In this paper we use a particular DL
formulation that seeks uniform sparse representations model to detect the
underlying subspace of the majority of samples in a dataset, …

anomaly detection arxiv detection dictionary for learning uniform

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