The DOI matches its Crossref record.
Global Convergence of a Cass of Quasi-Newton Methods on Convex Problems
Abstract
We study the global convergence properties of the restricted Broyden class of quasi-Newton methods, when applied to a convex objective function. We assume that the line search satisfies a standard sufficient decrease condition and that the initial Hessian approximation is any positive definite matrix. We show global and superlinear convergence for this class of methods, except for DFP. This generalizes Powell’s well-known result for the BFGS method. The analysis gives us insight into the properties of these algorithms; in particular it shows that DFP lacks a very desirable self-correcting property possessed by BFGS.
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
Deformable medical image registration: a survey
Sotiras, A., Davatzikos, C., & Paragios, N. (2013) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2013.2265603 · Cited by 1,587
Some numerical experiments with variable-storage quasi-Newton algorithms
Gilbert, J. C., & Lemaréchal, C. (1989) · Mathematical Programming · doi:10.1007/bf01589113 · Cited by 759
Metadata
- Authors
- Byrd, R. H., Nocedal, J., & Yuan, Y.-X.
- Venue
- SIAM Journal on Numerical Analysis
- Published
- 1987-10
- Volume
- 24
- Issue
- 5
- Pages
- 1171-1190
- ISSN
- 0036-1429 (ISSN-L)
- 1095-7170
- OpenAlex
- W2045968916
- Cited by
- 319
- References
- 0
- FWCI
- 4.59
- 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: Global Convergence of a Cass of Quasi-Newton Methods on Convex Problems. https://app.cochat.ai/papers/10.1137/0724077
- The paper
- Byrd, R. H., Nocedal, J., & Yuan, Y.-X. (1987). Global Convergence of a Cass of Quasi-Newton Methods on Convex Problems. SIAM Journal on Numerical Analysis. https://doi.org/10.1137/0724077
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.