Kuliah Umum 演講訊息

Abstract：

In this talk, we will see the fundamental ideas and tools needed to perform numerical optimization on matrix manifolds. We will introduce the main tools from Riemannian geometry that allow us to extend the classical steepest descent algorithm to matrix manifolds, with particular emphasis on retraction mapping, and present some numerical examples. To keep the presentation more concrete, we will use the Stiefel manifold as a running example, but the concepts discussed herein remain valid for any embedded submanifold. We will discuss applications on the Stifel manifold, the power manifold of unit spheres, and the manifold of fixed-rank matrices.

20241212演講_Dr. Marco Sutti (國家理論科學研究中心)