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math.OC2026
Acceleration via Perturbations on Low-resolution Ordinary Differential Equations
Xudong Li, Lei Shi, Mingqi Song
Recently, the high-resolution ordinary differential equation (ODE) framework, which retains higher-order terms, has been proposed to analyze gradient-based optimization algorithms.…
math.OC2025
Revisit First-order Methods for Geodesically Convex Optimization
Yunlu Shu, Jiaxin Jiang, Lei Shi +1
In a seminal work of Zhang and Sra, gradient descent methods for geodesically convex optimization were comprehensively studied. In particular, Zhang and Sra derived a comparison in…