2 papers
math.NA2021
Local convergence of alternating low-rank optimization methods with overrelaxation
Ivan V. Oseledets, Maxim V. Rakhuba, André Uschmajew
The local convergence of alternating optimization methods with overrelaxation for low-rank matrix and tensor problems is established. The analysis is based on the linearization of…
math.NA2017
Alternating least squares as moving subspace correction
Ivan Oseledets, Maxim Rakhuba, André Uschmajew
In this note we take a new look at the local convergence of alternating optimization methods for low-rank matrices and tensors. Our abstract interpretation as sequential optimizati…