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(2019.7.26)Prof. Long Chen:From differential equation solvers to first order convex optimization methods
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Update time: 2019-07-26
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Academy of Mathematics and Systems Science, CAS
Colloquia & Seminars

Speaker:

Prof. Long Chen, Univ of California at Irvine

Inviter:  
Title:
From differential equation solvers to first order convex optimization methods
Time & Venue:
2019.7.26 10:00-11:00 N202
Abstract:
Convergence analysis of accelerated first-order methods for convex optimization problems are presented from the point of view of ordinary differential equation (ODE) solvers. Two resolution ODEs are derived for accelerated gradient methods. Numerical discretizations for these resolution ODEs are considered and its convergence analyses are established via tailored Lyapunov functions. The ODE solvers approach can not only cover existing methods, such as Nesterov's accelerated gradient method and FISTA, but also produce a large class of new algorithms that possesses optimal convergence rates.

This is a joint work with Hao Luo from Sichuan University

 

 

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