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math.OC2025
Essential Convergence Rates of Continuous-Time Models for Optimization Methods
Kansei Ushiyama, Shun Sato, Takayasu Matsuo
Designing and analyzing optimization methods via continuous-time models expressed as ordinary differential equations (ODEs) is a promising approach for its intuitiveness and simpli…
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…