Related references
Note: Only part of the references are listed.Complexity analysis of interior point algorithms for non-Lipschitz and nonconvex minimization
Wei Bian et al.
MATHEMATICAL PROGRAMMING (2015)
On the convergence and worst-case complexity of trust-region and regularization methods for unconstrained optimization
Geovani N. Grapiglia et al.
MATHEMATICAL PROGRAMMING (2015)
Worst case complexity of direct search
L. N. Vicente
EURO JOURNAL ON COMPUTATIONAL OPTIMIZATION (2013)
An adaptive cubic regularization algorithm for nonconvex optimization with convex constraints and its function-evaluation complexity
C. Cartis et al.
IMA JOURNAL OF NUMERICAL ANALYSIS (2012)
Complexity bounds for second-order optimality in unconstrained optimization
C. Cartis et al.
JOURNAL OF COMPLEXITY (2012)
Evaluation complexity of adaptive cubic regularization methods for convex unconstrained optimization
Coralia Cartis et al.
OPTIMIZATION METHODS & SOFTWARE (2012)
Adaptive cubic regularisation methods for unconstrained optimization. Part I: motivation, convergence and numerical results
Coralia Cartis et al.
MATHEMATICAL PROGRAMMING (2011)
Adaptive cubic regularisation methods for unconstrained optimization. Part II: worst-case function- and derivative-evaluation complexity
Coralia Cartis et al.
MATHEMATICAL PROGRAMMING (2011)
CONVERGENCE OF A REGULARIZED EUCLIDEAN RESIDUAL ALGORITHM FOR NONLINEAR LEAST-SQUARES
S. Bellavia et al.
SIAM JOURNAL ON NUMERICAL ANALYSIS (2010)
ON THE COMPLEXITY OF STEEPEST DESCENT, NEWTON'S AND REGULARIZED NEWTON'S METHODS FOR NONCONVEX UNCONSTRAINED OPTIMIZATION PROBLEMS
C. Cartis et al.
SIAM JOURNAL ON OPTIMIZATION (2010)
Recursive trust-region methods for multiscale nonlinear optimization
Serge Gratton et al.
SIAM JOURNAL ON OPTIMIZATION (2008)
Modified Gauss-Newton scheme with worst case guarantees for global performance
Yu. Nesterov
OPTIMIZATION METHODS & SOFTWARE (2007)
Cubic regularization of Newton method and its global performance
Yurii Nesterov et al.
MATHEMATICAL PROGRAMMING (2006)
Share Paper
