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Our goal is to find anomalous features in a dataset using the sparse coding concept of dictionary learning. Rather than using the averaged column ℓ2-norm for the dictionary update as is typically done in sparse coding, we explore using three matrix norms: ∥·∥1, ∥·∥2, and ∥·∥∞. Minimizing the matrix norms represents minimizing a maximum deviation in the reconstruction error rather than an average deviation,...
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