The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Proximal alternating linearized minimization for nonconvex and nonsmooth problems
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Citations
Cites
A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
Beck, A., & Teboulle, M. (2009) · SIAM Journal on Imaging Sciences · doi:10.1137/080716542 · Cited by 11,952
Self-citation
Cited by
Wright, S. J. (2015) · Mathematical Programming · doi:10.1007/s10107-015-0892-3 · Cited by 1,438
Joint Optimization of Radio and Computational Resources for Multicell Mobile-Edge Computing
Sardellitti, S., Scutari, G., & Barbarossa, S. (2015) · IEEE Transactions on Signal and Information Processing over Networks · doi:10.1109/tsipn.2015.2448520 · Cited by 891
Shi, Q., & Hong, M. (2020) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2020.3001906 · Cited by 283
From error bounds to the complexity of first-order descent methods for convex functions
Bolte, J., Nguyen, T. P., Peypouquet, J., & Suter, B. W. (2017) · Mathematical Programming · doi:10.1007/s10107-016-1091-6 · Cited by 265
Self-citationComplete Dictionary Recovery Over the Sphere I: Overview and the Geometric Picture
Sun, J., Qu, Q., & Wright, J. (2017) · IEEE Transactions on Information Theory · doi:10.1109/tit.2016.2632162 · Cited by 213
Metadata
- Authors
- Bolte, J., Sabach, S., & Teboulle, M.
- Venue
- Mathematical Programming
- Published
- 2013-07-26
- Volume
- 146
- Issue
- 1-2
- Pages
- 459-494
- ISSN
- 0025-5610 (ISSN-L)
- 1436-4646
- OpenAlex
- W2027982384
- Cited by
- 1,688
- References
- 1
- FWCI
- 62.67
- Type
- journal article
- Language
- en
- Open access
- closed
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- The paper
- Bolte, J., Sabach, S., & Teboulle, M. (2014). Proximal alternating linearized minimization for nonconvex and nonsmooth problems. Mathematical Programming. https://doi.org/10.1007/s10107-013-0701-9
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
