Restarts subject to approximate sharpness: A parameter-free and optimal scheme for first-order methods

no code implementations • 5 Jan 2023 • Ben Adcock, Matthew J. Colbrook, Maksym Neyra-Nesterenko

However, sharpness involves problem-specific constants that are typically unknown, and previous restart schemes reduce convergence rates.

NESTANets: Stable, accurate and efficient neural networks for analysis-sparse inverse problems

1 code implementation • 2 Mar 2022 • Maksym Neyra-Nesterenko, Ben Adcock

With the advent of deep learning, deep neural networks have significant potential to outperform existing state-of-the-art, model-based methods for solving inverse problems.

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