2 papers
math.OC2023
A new unified framework for designing convex optimization methods with prescribed theoretical convergence estimates: A numerical analysis approach
Kansei Ushiyama, Shun Sato, Takayasu Matsuo
We propose a new unified framework for describing and designing gradient-based convex optimization methods from a numerical analysis perspective. There the key is the new concept o…
math.NA2022
Essential convergence rate of ordinary differential equations appearing in optimization
Kansei Ushiyama, Shun Sato, Takayasu Matsuo
Some continuous optimization methods can be connected to ordinary differential equations (ODEs) by taking continuous limits, and their convergence rates can be explained by the ODE…