The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Iterative Methods for Optimization
Abstract
This book presents a carefully selected group of methods for unconstrained and bound constrained optimization problems and analyzes them in depth both theoretically and algorithmically. It focuses on clarity in algorithmic description and analysis rather than generality, and while it provides pointers to the literature for the most general theoretical results and robust software, the author thinks it is more important that readers have a complete understanding of special cases that convey essential ideas. A companion to Kelley's book, Iterative Methods for Linear and Nonlinear Equations (SIAM, 1995), this book contains many exercises and examples and can be used as a text, a tutorial for self-study, or a reference. Iterative Methods for Optimization does more than cover traditional gradient-based optimization: it is the first book to treat sampling methods, including the Hooke& Jeeves, implicit filtering, MDS, and Nelder& Mead schemes in a unified way.
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Citations
Cites
Golub, G. (2012) · doi:10.56021/9781421407944 · Cited by 34,505
An Algorithm for Least-Squares Estimation of Nonlinear Parameters
Marquardt, D. W. (1963) · Journal of the Society for Industrial and Applied Mathematics · doi:10.1137/0111030 · Cited by 30,728
A Simplex Method for Function Minimization
Nelder, J. A., & Mead, R. (1965) · The Computer Journal · doi:10.1093/comjnl/7.4.308 · Cited by 28,905
Cited by
Derivative-free optimization: a review of algorithms and comparison of software implementations
Rios, L. M., & Sahinidis, N. V. (2013) · Journal of Global Optimization · doi:10.1007/s10898-012-9951-y · Cited by 1,276
SBA: A software package for generic sparse bundle adjustment
Lourakis, M. I. A., & Argyros, A. A. (2009) · ACM Transactions on Mathematical Software · doi:10.1145/1486525.1486527 · Cited by 788
Maier, H. R., Kapelan, Z., Kasprzyk, J., Kollat, J., Matott, L. S., Cunha, M. C., Dandy, G. C., Gibbs, M. S., Keedwell, E., Marchi, A., et al. (2014) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2014.09.013 · Cited by 657
Optimization problems for machine learning: A survey
Gambella, C., Ghaddar, B., & Naoum-Sawaya, J. (2021) · European Journal of Operational Research · doi:10.1016/j.ejor.2020.08.045 · Cited by 365
Exploiting Known Interference as Green Signal Power for Downlink Beamforming Optimization
Masouros, C., & Zheng, G. (2015) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2015.2430839 · Cited by 360
Metadata
- Authors
- Kelley, C. T.
- Venue
- Society for Industrial and Applied Mathematics eBooks
- Published
- 1999-01
- OpenAlex
- W2123224804
- Cited by
- 2,052
- References
- 3
- FWCI
- 3.18
- Type
- book
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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