most citedLow-rank optimization methods based on projected projected-gradient descent that accumulate at Bouligand stationary points

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math.OC2026★ 3 cited

Low-rank optimization methods based on projected projected-gradient descent that accumulate at Bouligand stationary points

Guillaume Olikier, Kyle A. Gallivan, P. -A. Absil

This paper considers the problem of minimizing a differentiable function with locally Lipschitz continuous gradient on the algebraic variety of real matrices of upper-bounded rank.…

math.OC2024

On the analysis of optimization with fixed-rank matrices: a quotient geometric view

Shuyu Dong, Bin Gao, Wen Huang +1

We study a type of Riemannian gradient descent (RGD) algorithm, designed through Riemannian preconditioning, for optimization on -- the set of $m\times…