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20172021
most citedCompression and Interpretability of Deep Neural Networks via Tucker Tensor Layer: From First Principles to Tensor Valued Back-Propagation

21 citations · 26 across the 8 of their papers we have counts for

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Showing 2019Show all

2 papers · 1 filter

eess.SP2019★ 1 cited

Tight Lower Bound on the Tensor Rank based on the Maximally Square Unfolding

Giuseppe G. Calvi, Bruno Scalzo Dees, Danilo P. Mandic

Tensors decompositions are a class of tools for analysing datasets of high dimensionality and variety in a natural manner, with the Canonical Polyadic Decomposition (CPD) being a m…

cs.LG2019★ 21 cited

Compression and Interpretability of Deep Neural Networks via Tucker Tensor Layer: From First Principles to Tensor Valued Back-Propagation

Giuseppe G. Calvi, Ahmad Moniri, Mahmoud Mahfouz +2

This work aims to help resolve the two main stumbling blocks in the application of Deep Neural Networks (DNNs), that is, the exceedingly large number of trainable parameters and th…