Low-Rank Tensor Decompositions for the Theory of Neural Networks: Understanding deep learning through the lens of tensor formats

The groundbreaking performance of deep neural networks (NNs) promoted a surge of interest in providing a mathematical basis to deep learning theory. Low-rank tensor decompositions are specially befitting for this task due to their close connection to NNs and their rich theoretical results. Different