Pages that link to "Item:Q2494519"
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The following pages link to Cubic regularization of Newton method and its global performance (Q2494519):
Displaying 50 items.
- Practical inexact proximal quasi-Newton method with global complexity analysis (Q344963) (← links)
- Global complexity bound analysis of the Levenberg-Marquardt method for nonsmooth equations and its application to the nonlinear complementarity problem (Q415364) (← links)
- A trust region algorithm with adaptive cubic regularization methods for nonsmooth convex minimization (Q429459) (← links)
- Interior-point methods for nonconvex nonlinear programming: cubic regularization (Q457205) (← links)
- Nonlinear stepsize control algorithms: complexity bounds for first- and second-order optimality (Q504812) (← links)
- A trust region algorithm with a worst-case iteration complexity of \(\mathcal{O}(\epsilon ^{-3/2})\) for nonconvex optimization (Q517288) (← links)
- Worst-case evaluation complexity for unconstrained nonlinear optimization using high-order regularized models (Q526842) (← links)
- Adaptive cubic regularisation methods for unconstrained optimization. I: Motivation, convergence and numerical results (Q535013) (← links)
- On a global complexity bound of the Levenberg-marquardt method (Q620432) (← links)
- Adaptive cubic regularisation methods for unconstrained optimization. II: Worst-case function- and derivative-evaluation complexity (Q652287) (← links)
- Complexity bounds for second-order optimality in unconstrained optimization (Q657654) (← links)
- Updating the regularization parameter in the adaptive cubic regularization algorithm (Q694543) (← links)
- A regularized Newton method without line search for unconstrained optimization (Q742310) (← links)
- Worst case complexity of direct search (Q743632) (← links)
- Separable cubic modeling and a trust-region strategy for unconstrained minimization with impact in global optimization (Q746819) (← links)
- On solving trust-region and other regularised subproblems in optimization (Q977328) (← links)
- Accelerating the cubic regularization of Newton's method on convex problems (Q995787) (← links)
- Trust-region and other regularisations of linear least-squares problems (Q1014897) (← links)
- Regularized Newton method for unconstrained convex optimization (Q1016344) (← links)
- Precision, complexity, and computational schemes of the cubic algorithms (Q1090611) (← links)
- Global convergence rate analysis of unconstrained optimization methods based on probabilistic models (Q1646566) (← links)
- Cubic-regularization counterpart of a variable-norm trust-region method for unconstrained minimization (Q1675558) (← links)
- Folded concave penalized sparse linear regression: sparsity, statistical performance, and algorithmic theory for local solutions (Q1683689) (← links)
- On the use of the energy norm in trust-region and adaptive cubic regularization subproblems (Q1694391) (← links)
- On the worst-case evaluation complexity of non-monotone line search algorithms (Q1694392) (← links)
- Conjugate direction methods and polarity for quadratic hypersurfaces (Q1695819) (← links)
- A line-search algorithm inspired by the adaptive cubic regularization framework and complexity analysis (Q1730832) (← links)
- Sub-sampled Newton methods (Q1739039) (← links)
- Cubic regularization in symmetric rank-1 quasi-Newton methods (Q1741108) (← links)
- Second-order optimality and beyond: characterization and evaluation complexity in convexly constrained nonlinear optimization (Q1785005) (← links)
- A geometric analysis of phase retrieval (Q1785008) (← links)
- Complexity bounds for primal-dual methods minimizing the model of objective function (Q1785201) (← links)
- Fine tuning Nesterov's steepest descent algorithm for differentiable convex programming (Q1949275) (← links)
- The global optimization geometry of shallow linear neural networks (Q1988338) (← links)
- Optimality of orders one to three and beyond: characterization and evaluation complexity in constrained nonconvex optimization (Q2001208) (← links)
- A Newton-like trust region method for large-scale unconstrained nonconvex minimization (Q2015579) (← links)
- Regional complexity analysis of algorithms for nonconvex smooth optimization (Q2020615) (← links)
- Worst-case complexity bounds of directional direct-search methods for multiobjective optimization (Q2026717) (← links)
- A generalized worst-case complexity analysis for non-monotone line searches (Q2028039) (← links)
- Decentralized optimization over tree graphs (Q2031996) (← links)
- Minimizing uniformly convex functions by cubic regularization of Newton method (Q2032037) (← links)
- Adaptive regularization with cubics on manifolds (Q2039233) (← links)
- New subspace minimization conjugate gradient methods based on regularization model for unconstrained optimization (Q2041515) (← links)
- An accelerated first-order method with complexity analysis for solving cubic regularization subproblems (Q2044484) (← links)
- Adaptive regularization for nonconvex optimization using inexact function values and randomly perturbed derivatives (Q2052165) (← links)
- A two-step improved Newton method to solve convex unconstrained optimization problems (Q2053267) (← links)
- On large-scale unconstrained optimization and arbitrary regularization (Q2070329) (← links)
- An adaptive high order method for finding third-order critical points of nonconvex optimization (Q2079692) (← links)
- On complexity and convergence of high-order coordinate descent algorithms for smooth nonconvex box-constrained minimization (Q2089862) (← links)
- On local nonglobal minimum of trust-region subproblem and extension (Q2093294) (← links)
