Stochastic Primal–Dual Hybrid Gradient Algorithm with Adaptive Step Sizes

In this work, we propose a new primal–dual algorithm with adaptive step sizes. The stochastic primal–dual hybrid gradient (SPDHG) algorithm with constant step sizes has become widely applied in large-scale convex optimization across many scientific fields due to its scalability. While the product of...

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Bibliographic Details

Published in:	Journal of mathematical imaging and vision Vol. 66; no. 3; pp. 294 - 313
Main Authors:	Chambolle, Antonin, Delplancke, Claire, Ehrhardt, Matthias J., Schönlieb, Carola-Bibiane, Tang, Junqi
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.06.2024 Springer Nature B.V Springer Verlag
Subjects:	Adaptive algorithms Algorithms Applications of Mathematics Computed tomography Computer Science Convergence Convex analysis Convexity Image Processing and Computer Vision Inverse problems Mathematical Methods in Physics Mathematics Signal,Image and Speech Processing Upper bounds
ISSN:	0924-9907, 1573-7683
Online Access:	Get full text
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