Title
On the Evaluation Complexity of Cubic Regularization Methods for Potentially Rank-Deficient Nonlinear Least-Squares Problems and Its Relevance to Constrained Nonlinear Optimization.
Abstract
We propose a new termination criterion suitable for potentially singular, zero or nonzero residual, least-squares problems, with which cubic regularization variants take at most O(epsilon(-3/2)) residual- and Jacobian-evaluations to drive either the Euclidean norm of the residual or its gradient below epsilon; this is the best known bound for potentially rank-deficient nonlinear least-squares problems. We then apply the new optimality measure and cubic regularization steps to a family of least-squares merit functions in the context of a target-following algorithm for nonlinear equality-constrained problems; this approach yields the first evaluation complexity bound of order epsilon(-3/2) for nonconvexly constrained problems when higher accuracy is required for primal feasibility than for dual first-order criticality.
Year
DOI
Venue
2013
10.1137/120869687
SIAM JOURNAL ON OPTIMIZATION
Keywords
Field
DocType
evaluation complexity,worst-case analysis,least-squares problems,constrained nonlinear optimization,cubic regularization methods
Trust region,Residual,Discrete mathematics,Mathematical optimization,Nonlinear system,Nonlinear programming,Euclidean distance,Regularization (mathematics),Non-linear least squares,Mathematics,Penalty method
Journal
Volume
Issue
ISSN
23
3
1052-6234
Citations 
PageRank 
References 
8
0.63
12
Authors
3
Name
Order
Citations
PageRank
Coralia Cartis145128.74
Nicholas I. M. Gould21445123.86
Philippe L. Toint31397127.90