The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
A feasible method for optimization with orthogonality constraints
Overview
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Citations
Cites
Golub, G. (2012) · doi:10.56021/9781421407944 · Cited by 34,505
Cited by
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Wu, G., Han, J., Guo, Y., Liu, L., Ding, G., Ni, Q., & Shao, L. (2019) · IEEE Transactions on Image Processing · doi:10.1109/tip.2018.2882155 · Cited by 148
Learning to Hash With Optimized Anchor Embedding for Scalable Retrieval
Guo, Y., Ding, G., Liu, L., Han, J., & Shao, L. (2017) · IEEE Transactions on Image Processing · doi:10.1109/tip.2017.2652730 · Cited by 108
Enhancing Explainability of Neural Networks Through Architecture Constraints
Yang, Z., Zhang, A., & Sudjianto, A. (2021) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2020.3007259 · Cited by 106
Metadata
- Authors
- Wen, Z., & Yin, W.
- Venue
- Mathematical Programming
- Published
- 2012-08-29
- Volume
- 142
- Issue
- 1-2
- Pages
- 397-434
- ISSN
- 0025-5610 (ISSN-L)
- 1436-4646
- OpenAlex
- W2086953401
- Cited by
- 849
- References
- 1
- FWCI
- 37.09
- 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 ›
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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.
