Bregman Methods for Large-Scale Optimization with Applications in Imaging
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Published version
Embargoed until: 5555-01-01
Reason: Version not permitted.
Embargoed until: 5555-01-01
Reason: Version not permitted.
Pagination
97 - 138
ISBN-13
9783030986605
DOI
10.1007/978-3-030-98661-2_62
Journal
Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging: Mathematical Imaging and Vision
Metadata
Show full item recordAbstract
In this chapter we review recent developments in the research of Bregman methods, with particular focus on their potential use for large-scale applications. We give an overview on several families of Bregman algorithms and discuss modifications such as accelerated Bregman methods, incremental and stochastic variants, and coordinate descent-type methods. We conclude this chapter with numerical examples in image and video decomposition, image denoising, and dimensionality reduction with auto-encoders.
Authors
Benning, M; Riis, ESCollections
- Mathematics [1463]