Pages that link to "Item:Q1646566"

The following pages link to Global convergence rate analysis of unconstrained optimization methods based on probabilistic models (Q1646566):

Displaying 50 items.

• Second-order optimality and beyond: characterization and evaluation complexity in convexly constrained nonlinear optimization (Q1785005) (← links)
• Optimality of orders one to three and beyond: characterization and evaluation complexity in constrained nonconvex optimization (Q2001208) (← links)
• An algorithm for the minimization of nonsmooth nonconvex functions using inexact evaluations and its worst-case complexity (Q2020598) (← links)
• Regional complexity analysis of algorithms for nonconvex smooth optimization (Q2020615) (← links)
• Stochastic mesh adaptive direct search for blackbox optimization using probabilistic estimates (Q2028452) (← links)
• An accelerated directional derivative method for smooth stochastic convex optimization (Q2029381) (← links)
• Minimizing uniformly convex functions by cubic regularization of Newton method (Q2032037) (← links)
• A stochastic subspace approach to gradient-free optimization in high dimensions (Q2044475) (← links)
• Adaptive regularization for nonconvex optimization using inexact function values and randomly perturbed derivatives (Q2052165) (← links)
• Linesearch Newton-CG methods for convex optimization with noise (Q2084588) (← links)
• A stochastic first-order trust-region method with inexact restoration for finite-sum minimization (Q2111466) (← links)
• Smoothness parameter of power of Euclidean norm (Q2178876) (← links)
• A note on solving nonlinear optimization problems in variable precision (Q2191797) (← links)
• Newton-type methods for non-convex optimization under inexact Hessian information (Q2205970) (← links)
• Affine-invariant contracting-point methods for convex optimization (Q2687041) (← links)
• Bound-constrained global optimization of functions with low effective dimensionality using multiple random embeddings (Q2687068) (← links)
• Adaptive Sampling Strategies for Stochastic Optimization (Q4562248) (← links)
• Global Convergence Rate Analysis of a Generic Line Search Algorithm with Noise (Q4997171) (← links)
• Stochastic analysis of an adaptive cubic regularization method under inexact gradient evaluations and dynamic Hessian accuracy (Q5034938) (← links)
• A fully stochastic second-order trust region method (Q5043844) (← links)
• A Variable Sample-Size Stochastic Quasi-Newton Method for Smooth and Nonsmooth Stochastic Convex Optimization (Q5076721) (← links)
• Stochastic Trust-Region Methods with Trust-Region Radius Depending on Probabilistic Models (Q5079553) (← links)
• Global Linear Convergence of Evolution Strategies on More than Smooth Strongly Convex Functions (Q5081786) (← links)
• Streaming Principal Component Analysis From Incomplete Data (Q5214169) (← links)
• A Stochastic Line Search Method with Expected Complexity Analysis (Q5215517) (← links)
• Derivative-free optimization methods (Q5230522) (← links)
• An Inexact Variable Metric Proximal Point Algorithm for Generic Quasi-Newton Acceleration (Q5231671) (← links)
• Adaptive Regularization Algorithms with Inexact Evaluations for Nonconvex Optimization (Q5244400) (← links)
• High-Order Optimization Methods for Fully Composite Problems (Q5869820) (← links)
• Scalable subspace methods for derivative-free nonlinear least-squares optimization (Q6038650) (← links)
• An adaptive stochastic sequential quadratic programming with differentiable exact augmented Lagrangians (Q6038658) (← links)
• Zeroth-order optimization with orthogonal random directions (Q6038668) (← links)
• Inequality constrained stochastic nonlinear optimization via active-set sequential quadratic programming (Q6052061) (← links)
• A trust region method for noisy unconstrained optimization (Q6052069) (← links)
• Direct Search Based on Probabilistic Descent in Reduced Spaces (Q6071887) (← links)
• An adaptive sampling augmented Lagrangian method for stochastic optimization with deterministic constraints (Q6072951) (← links)
• Convergence Properties of an Objective-Function-Free Optimization Regularization Algorithm, Including an \(\boldsymbol{\mathcal{O}(\epsilon^{-3/2})}\) Complexity Bound (Q6116246) (← links)
• Adaptive sampling stochastic multigradient algorithm for stochastic multiobjective optimization (Q6142067) (← links)
• Global optimization using random embeddings (Q6160282) (← links)
• Trust-region algorithms: probabilistic complexity and intrinsic noise with applications to subsampling techniques (Q6170037) (← links)
• Adaptive sampling quasi-Newton methods for zeroth-order stochastic optimization (Q6175706) (← links)
• Gradient regularization of Newton method with Bregman distances (Q6201850) (← links)
• Derivative-free separable quadratic modeling and cubic regularization for unconstrained optimization (Q6489314) (← links)
• Stochastic trust-region and direct-search methods: a weak tail bound condition and reduced sample sizing (Q6561380) (← links)
• High probability complexity bounds for adaptive step search based on stochastic oracles (Q6573017) (← links)
• Inexact tensor methods and their application to stochastic convex optimization (Q6585820) (← links)
• Subsampled first-order optimization methods with applications in imaging (Q6606441) (← links)
• First- and second-order high probability complexity bounds for trust-region methods with noisy oracles (Q6608030) (← links)
• An investigation of stochastic trust-region based algorithms for finite-sum minimization (Q6644989) (← links)
• A sequential quadratic programming method with high-probability complexity bounds for nonlinear equality-constrained stochastic optimization (Q6663117) (← links)