There has been growing interest in high-order tensor methods for nonconv...
We propose a Randomised Subspace Gauss-Newton (R-SGN) algorithm for solv...
We investigate the problem of recovering a partially observed high-rank
...
We propose a random-subspace algorithmic framework for global optimizati...
The aim of this paper is two-fold: firstly, to present subspace embeddin...
We provide sharp worst-case evaluation complexity bounds for nonconvex
m...
The unconstrained minimization of a sufficiently smooth objective functi...