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Overall Objectives
New Software and Platforms
New Results
Bilateral Contracts and Grants with Industry
Bibliography
Overall Objectives
New Software and Platforms
New Results
Bilateral Contracts and Grants with Industry
Bibliography


Section: New Results

Lyapunov Functions for First-Order Methods: Tight Automated Convergence Guarantees

In [21], we present a novel way of generating Lyapunov functions for proving linear convergence rates of first-order optimization methods. Our approach provably obtains the fastest linear convergence rate that can be verified by a quadratic Lyapunov function (with given states), and only relies on solving a small-sized semidefinite program. Our approach combines the advantages of performance estimation problems and integral quadratic constraints, and relies on convex interpolation.