The DOI matches its Crossref record.
On Projection Algorithms for Solving Convex Feasibility Problems
Abstract
Due to their extraordinary utility and broad applicability in many areas of classical mathematics and modern physical sciences (most notably, computerized tomography), algorithms for solving convex feasibility problems continue to receive great attention. To unify, generalize, and review some of these algorithms, a very broad and flexible framework is investigated. Several crucial new concepts which allow a systematic discussion of questions on behaviour in general Hilbert spaces and on the quality of convergence are brought out. Numerous examples are given.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Boyd, S., Parikh, N., Chu, E., Peleato, B., & Eckstein, J. (2011) · Foundations and Trends® in Machine Learning · doi:10.1561/2200000016 · Cited by 17,075
Parikh, N., & Boyd, S. (2014) · Foundations and Trends® in Optimization · doi:10.1561/2400000003 · Cited by 4,102
TEASER: Fast and Certifiable Point Cloud Registration
Yang, H., Shi, J., & Carlone, L. (2021) · IEEE Transactions on Robotics · doi:10.1109/tro.2020.3033695 · Cited by 895
Error bounds in mathematical programming
Pang, J.-S. (1997) · Mathematical Programming · doi:10.1007/bf02614322 · Cited by 441
Metadata
- Authors
- Bauschke, H. H., & Borwein, J. M.
- Venue
- SIAM Review
- Published
- 1996-09
- Volume
- 38
- Issue
- 3
- Pages
- 367-426
- ISSN
- 0036-1445 (ISSN-L)
- 1095-7200
- OpenAlex
- W2033511209
- Cited by
- 1,654
- References
- 0
- FWCI
- 22.67
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: On Projection Algorithms for Solving Convex Feasibility Problems. https://app.cochat.ai/papers/10.1137/s0036144593251710
- The paper
- Bauschke, H. H., & Borwein, J. M. (1996). On Projection Algorithms for Solving Convex Feasibility Problems. SIAM Review. https://doi.org/10.1137/s0036144593251710
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
