Bregman Methods for Large-Scale Optimisation with Applications in Imaging
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Published version
Embargoed until: 5555-01-01
Embargoed until: 5555-01-01
Editors
Chen, K
Schönlieb, C-B
Tai, X-C
Younes, L
Pagination
1 - 42
Publisher
DOI
10.1007/978-3-030-03009-4_62-1
Journal
Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging
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 [1485]
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