
Learning Low-Rank Approximation for CNNs
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AI paper review/Model Compression
1. Introduction Filter Decomposition (FD): Decomposing a weight tensor into multiple tensors to be multiplied in a consecutive manner and then getting a compressed model. 1.1 Motivation Well-known low-rank approximation (i.e. FD) methods, such as Tucker or CP decomposition, result in degraded model accuracy because decomposed layers hinder training convergence. 1.2 Goal To tackle this problem, t..