most citedRandomised subspace methods for non-convex optimization, with applications to nonlinear least-squares

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

collaborators

3 papers

math.OC2025

Random Subspace Cubic-Regularization Methods, with Applications to Low-Rank Functions

Coralia Cartis, Zhen Shao, Edward Tansley

We propose and analyze random subspace variants of the second-order Adaptive Regularization using Cubics (ARC) algorithm. These methods iteratively restrict the search space to som…

math.OC2022★ 3 cited

Randomised subspace methods for non-convex optimization, with applications to nonlinear least-squares

Coralia Cartis, Jaroslav Fowkes, Zhen Shao

We propose a general random subspace framework for unconstrained nonconvex optimization problems that requires a weak probabilistic assumption on the subspace gradient, which we sh…

math.OC2022★ 1 cited

A Randomised Subspace Gauss-Newton Method for Nonlinear Least-Squares

Coralia Cartis, Jaroslav Fowkes, Zhen Shao

We propose a Randomised Subspace Gauss-Newton (R-SGN) algorithm for solving nonlinear least-squares optimization problems, that uses a sketched Jacobian of the residual in the vari…