Result 1 to 20 of 119 total
An adaptive cubic regularization algorithm for nonconvex optimization with convex constraints and its function-evaluation complexity. (English)
IMA J. Numer. Anal. 32, No. 4, 1662-1695 (2012).
1
On the oracle complexity of first-order and derivative-free algorithms for smooth nonconvex minimization. (English)
SIAM J. Optim. 22, No. 1, 66-86 (2012).
2
Erratum to: “Nonlinear programming without a penalty function or a filter”. (English)
Math. Program. 131, No. 1-2(A), 403-404 (2012).
3
Complexity bounds for second-order optimality in unconstrained optimization. (English)
J. Complexity 28, No. 1, 93-108 (2012).
4
Fast regularized linear sampling for inverse scattering problems. (English)
Numer. Linear Algebra Appl. 18, No. 1, 55-68 (2011).
5
On the evaluation complexity of composite function minimization with applications to nonconvex nonlinear programming. (English)
SIAM J. Optim. 21, No. 4, 1721-1739 (2011).
6
Range-space variants and inexact matrix-vector products in Krylov solvers for linear systems arising from inverse problems. (English)
SIAM J. Matrix Anal. Appl. 32, No. 3, 969-986 (2011).
7
Adaptive cubic regularisation methods for unconstrained optimization. II: Worst-case function- and derivative-evaluation complexity. (English)
Math. Program. 130, No. 2 (A), 295-319 (2011).
8
Stopping rules and backward error analysis for bound-constrained optimization. (English)
Numer. Math. 119, No. 1, 163-187 (2011).
9
Adaptive cubic regularisation methods for unconstrained optimization. I: Motivation, convergence and numerical results. (English)
Math. Program. 127, No. 2 (A), 245-295 (2011).
10
Range-space variants and inexact matrix-vector products in Krylov solvers for linear systems arising from inverse problems (English)
SIAM J. Matrix Analysis Applications 32, No. 3, 969-986 (2011).
11
Self-correcting geometry in model-based algorithms for derivative-free unconstrained optimization. (English)
SIAM J. Optim. 20, No. 6, 3512-3532 (2010).
12
On the complexity of steepest descent, Newton’s and regularized Newton’s methods for nonconvex unconstrained optimization problems. (English)
SIAM J. Optim. 20, No. 6, 2833-2852 (2010).
13
Convergence of a regularized Euclidean residual algorithm for nonlinear least-squares. (English)
SIAM J. Numer. Anal. 48, No. 1, 1-29 (2010).
14
Numerical experience with a recursive trust-region method for multilevel nonlinear bound-constrained optimization. (English)
Optim. Methods Softw. 25, No. 3, 359-386 (2010).
15
A retrospective trust-region method for unconstrained optimization. (English)
Math. Program. 123, No. 2 (A), 395-418 (2010).
16
Nonlinear programming without a penalty function or a filter. (English)
Math. Program. 122, No. 1 (A), 155-196 (2010); erratum ibid. 131, No. 1-2(A), 403-404 (2012).
17
Self-correcting geometry in model-based algorithms for derivative-free unconstrained optimization (English)
SIAM Journal on Optimization 20, No. 6, 3512-3532 (2010).
18
On the complexity of steepest descent, Newton’s and regularized Newton’s methods for nonconvex unconstrained optimization problems (English)
SIAM Journal on Optimization 20, No. 6, 2833-2852 (2010).
19
Convergence of a regularized Euclidean residual algorithm for nonlinear least-squares (English)
SIAM J. Numerical Analysis 48, No. 1, 1-29 (2010).
20
Result 1 to 20 of 119 total
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