Direct Search Based on Probabilistic Descent in Reduced Spaces
From MaRDI portal
Publication:6071887
DOI10.1137/22m1488569zbMath1528.90284arXiv2204.01275OpenAlexW4388573921MaRDI QIDQ6071887
Publication date: 29 November 2023
Published in: SIAM Journal on Optimization (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2204.01275
Abstract computational complexity for mathematical programming problems (90C60) Derivative-free methods and methods using generalized derivatives (90C56) Randomized algorithms (68W20)
Cites Work
- Unnamed Item
- Unnamed Item
- On the optimal order of worst case complexity of direct search
- Sharp nonasymptotic bounds on the norm of random matrices with independent entries
- Worst case complexity of direct search
- Global convergence rate analysis of unconstrained optimization methods based on probabilistic models
- A stochastic subspace approach to gradient-free optimization in high dimensions
- A deterministic algorithm to compute the cosine measure of a finite positive spanning set
- CUTEst: a constrained and unconstrained testing environment with safe threads for mathematical optimization
- Random gradient-free minimization of convex functions
- Direct search based on probabilistic feasible descent for bound and linearly constrained problems
- Trust-Region Methods Without Using Derivatives: Worst Case Complexity and the NonSmooth Case
- On the Oracle Complexity of First-Order and Derivative-Free Algorithms for Smooth Nonconvex Minimization
- Convergence of Trust-Region Methods Based on Probabilistic Models
- Optimal Rates for Zero-Order Convex Optimization: The Power of Two Function Evaluations
- Sparser Johnson-Lindenstrauss Transforms
- Introduction to Derivative-Free Optimization
- Smallest singular value of a random rectangular matrix
- Complexity and global rates of trust-region methods based on probabilistic models
- Derivative-Free and Blackbox Optimization
- Improving the Flexibility and Robustness of Model-based Derivative-free Optimization Solvers
- Stochastic Three Points Method for Unconstrained Smooth Minimization
- A Stochastic Line Search Method with Expected Complexity Analysis
- Derivative-free optimization methods
- Direct Search Based on Probabilistic Descent
- Benchmarking optimization software with performance profiles.
- Scalable subspace methods for derivative-free nonlinear least-squares optimization
- Zeroth-order optimization with orthogonal random directions
