3 papers
math.OC2022
Manifold Free Riemannian Optimization
Boris Shustin, Haim Avron, Barak Sober
Riemannian optimization is a principled framework for solving optimization problems where the desired optimum is constrained to a smooth manifold . Algorithms designed…
math.NA2021
Faster Randomized Methods for Orthogonality Constrained Problems
Boris Shustin, Haim Avron
Recent literature has advocated the use of randomized methods for accelerating the solution of various matrix problems arising throughout data science and computational science. On…
math.NA2019
Riemannian optimization with a preconditioning scheme on the generalized Stiefel manifold
Boris Shustin, Haim Avron
Optimization problems on the generalized Stiefel manifold (and products of it) are prevalent across science and engineering. For example, in computational science they arise in sym…