Large-scale derivative-free optimization using random subspace methods

20th IMA Leslie Fox Prize - Scalable Subscape Methods for Derivative-Free NLS OptimizationПодробнее

SESOP - sequential subspace optimization method for large-scale optimization problemsПодробнее

A Derivative-Free Trust-Region Method for Biobjective OptimizationПодробнее

Optimization in Machine Learning - Derivative Free Optimization - Multi-Start OptimizationПодробнее

Clément Royer, Optimization without derivatives in larger dimensions and across networksПодробнее

adaptive step size rules for stochastic optimization in largeПодробнее

Lindon Roberts: Derivative-Free Optimization with Convex Constraints}{Подробнее

UTRC CDS Lecture: Laurent Lessard, "Automating analysis & design of large optimization algorithms"Подробнее

Introduction to large-scale optimization - Part1Подробнее

Deep RL Bootcamp Lecture 8 Derivative Free MethodsПодробнее

Laura Grigori - Randomization techniques for solving large scale linear algebra problemsПодробнее

OiO Seminar (November 2, 2022) by Prof. Coralia CartisПодробнее

Derivative-free OptimisationПодробнее

17 - Derivative free optimizationПодробнее

Derivative-free optimisation for least-squares problems, Dr Lindon Roberts (ANU)Подробнее

[RMT + NLA] Carolia Cartis: Sparse random embeddings and their applications to optimizationПодробнее

Jorge Nocedal: "Tutorial on Optimization Methods for Machine Learning, Pt. 2"Подробнее

A. Beznosikov "A Derivative Free Method for Distributed Optimization"Подробнее

Fast Nonlinear Least Squares Optimization of Large Scale Semi Sparse ProblemsПодробнее