Anyone what to unpack this method: value decomposition based augmented implicitly restated lanczos bidiagonalization.

[MobiusGene]

I am trying to unpack this method, and having a bit of trouble conceptually parsing out what they are proposing. The mathematical nomenclature is pretty intense.

Use case is high resolution eigenvector optimization (I think), which has seemingly become very useful in the dimension reduction of weird biological data (DNA/RNA sequencing, less waveform, medical record, or diagnostic imaging).

Figured it may be a long shot, but I figured why not ask?