Automatic differentiation for Riemannian optimization on low-rank matrix and tensor-train manifolds

Alexander Novikov, Maxim Rakhuba, Ivan Oseledets

In scientific computing and machine learning applications, matrices and more general multidimensional arrays (tensors) can often be approximated with the help of low-rank decomposi…