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Title
Scalable adaptive cubic regularization methods
Authors
Keywords
-
Journal
MATHEMATICAL PROGRAMMING
Volume -, Issue -, Pages -
Publisher
Springer Science and Business Media LLC
Online
2023-10-31
DOI
10.1007/s10107-023-02007-6
References
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Related references
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- Worst-case evaluation complexity for unconstrained nonlinear optimization using high-order regularized models
- (2016) E. G. Birgin et al. MATHEMATICAL PROGRAMMING
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- CUTEst: a Constrained and Unconstrained Testing Environment with safe threads for mathematical optimization
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- On the Evaluation Complexity of Cubic Regularization Methods for Potentially Rank-Deficient Nonlinear Least-Squares Problems and Its Relevance to Constrained Nonlinear Optimization
- (2013) Coralia Cartis et al. SIAM JOURNAL ON OPTIMIZATION
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- (2011) N. I. M. Gould et al. COMPUTATIONAL OPTIMIZATION AND APPLICATIONS
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- LSMR: An Iterative Algorithm for Sparse Least-Squares Problems
- (2011) David Chin-Lung Fong et al. SIAM JOURNAL ON SCIENTIFIC COMPUTING
- Adaptive cubic regularisation methods for unconstrained optimization. Part II: worst-case function- and derivative-evaluation complexity
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- Adaptive cubic regularisation methods for unconstrained optimization. Part I: motivation, convergence and numerical results
- (2009) Coralia Cartis et al. MATHEMATICAL PROGRAMMING
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