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Numerical methods for least squares problems
Abstract
Preface 1. Mathematical and statistical properties of least squares solutions 2. Basic numerical methods 3. Modified least squares problems 4. Generalized least squares problems 5. Constrained least squares problems 6. Direct methods for sparse problems 7. Iterative methods for least squares problems 8. Least squares problems with special bases 9. Nonlinear least squares problems Bibliography Index.
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Cited by
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
Bundle Adjustment — A Modern Synthesis
Triggs, B., McLauchlan, P. F., Hartley, R. I., & Fitzgibbon, A. W. (2000) · Lecture Notes in Computer Science · doi:10.1007/3-540-44480-7_21 · Cited by 3,988
Subspace Pursuit for Compressive Sensing Signal Reconstruction
Dai, W., & Milenkovic, O. (2009) · IEEE Transactions on Information Theory · doi:10.1109/tit.2009.2016006 · Cited by 2,388
On the mathematical foundations of learning
Cucker, F., & Smale, S. (2001) · Bulletin of the American Mathematical Society · doi:10.1090/s0273-0979-01-00923-5 · Cited by 1,545
Beyond Nyquist: Efficient Sampling of Sparse Bandlimited Signals
Tropp, J. A., Laska, J. N., Duarte, M. F., Romberg, J. K., & Baraniuk, R. G. (2010) · IEEE Transactions on Information Theory · doi:10.1109/tit.2009.2034811 · Cited by 1,089
Metadata
- Venue
- Choice Reviews Online
- Publisher
- American Library Association
- Published
- 1996-11-01
- Volume
- 34
- Issue
- 03
- Pages
- 34-1602-34-1602
- ISSN
- 0009-4978 (ISSN-L)
- 1523-8253
- OpenAlex
- W2010315317
- Cited by
- 3,007
- References
- 0
- Type
- book review
- Language
- en
- Open access
- closed
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- Numerical methods for least squares problems. (1996). Choice Reviews Online. https://doi.org/10.5860/choice.34-1602
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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.
