Abstract: There is a vast literature on representation learning based on principles such as coding efficiency, statistical independence, causality, controllability, or symmetry. In this paper we ...
Abstract: Low-Rank Approximation (LRA) is a commonly used method for compressing deep learning (DL) models by factorizing weight matrices into lower-dimensional components. Although LRA is most ...
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