My M.Sc. thesis on big data learning with tensor representation, explained one part at a time. For quick definitions, see the tensor guides.
The t-SVD quietly assumes your data wraps around along its third mode. Swapping that for a mirror boundary gives the tc-product and tc-SVD: real arithmetic through the DCT and consistently shorter run times.
Mahdi Molavi
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Tensors have more than one SVD, and each one gives something up. A tour of Tucker, CP and the t-product behind t-SVD, with a short NumPy implementation you can run.
Mahdi Molavi
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Most machine learning pipelines turn images and videos into long vectors and lose their structure on the way. A plain introduction to tensors: modes, fibers, slices, unfolding and the mode-n product.
Mahdi Molavi
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My M.Sc. thesis keeps big data in tensor form and learns from it directly with tc-SVD, a cosine-transform tensor SVD. This page summarizes the thesis and links the Tensor Notes series that explains it.
Mahdi Molavi
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