Acceleration in First Order Quasi-strongly Convex Optimization by ODE Discretization

Acceleration in First Order Quasi-strongly Convex Optimization by ODE Discretization

We study gradient-based optimization methods obtained by direct Runge-Kutta discretization of the ordinary differential equation (ODE) describing the movement of a heavy-ball under constant friction coefficient. When the function is high-order smooth and strongly convex, we show that directly simula...

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Bibliographic Details
Main Authors: Zhang, Jingzhao, Sra, Suvrit, Jadbabaie, Ali
Other Authors: Massachusetts Institute of Technology. Laboratory for Information and Decision Systems
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE) 2021
Online Access:https://hdl.handle.net/1721.1/130426

Internet

https://hdl.handle.net/1721.1/130426

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