most citedNote: low-rank tensor train completion with side information based on Riemannian optimization

4 citations · 4 across the 2 of their papers we have counts for

collaborators

2 papers

math.NA2022

On the algorithm of best approximation by low rank matrices in the Chebyshev norm

Stanislav Morozov, Nikolai Zamarashkin, Eugene Tyrtyshnikov

The low-rank matrix approximation problem is ubiquitous in computational mathematics. Traditionally, this problem is solved in spectral or Frobenius norms, where the accuracy of th…

math.NA2020★ 4 cited

Note: low-rank tensor train completion with side information based on Riemannian optimization

Stanislav Budzinskiy, Nikolai Zamarashkin

We consider the low-rank tensor train completion problem when additional side information is available in the form of subspaces that contain the mode- fiber spans. We propose an…