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Author

Bartolomeo Stellato

Princeton University

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Preprint Oct 2026

The exact worst-case asymptotic rate of Nesterov acceleration for strongly convex optimization

We study Nesterov's accelerated gradient method with its standard constant parameters for smooth strongly convex optimization. We characterize the exact worst-case asymptotic factor for the squared distance to the minimizer. To this end, we construct candidate worst-case trajectories by combining planar spirals with a...

Sebastian Pokutta, Bartolomeo Stellato · 0 citations
Open access Jul 2026

Learning Algorithm Hyperparameters for Fast Parametric Convex Optimization

A machine-learning framework to learn the hyperparameter sequence of first-order methods to quickly solve parametric convex optimization problems, and shows how to learn hyperparameters for several popular algorithms: gradient descent, proximal gradient descent, and two ADMM-based solvers.

Rajiv Sambharya, Bartolomeo Stellato · 0 citations

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