Learning to optimize: A primer and a benchmark
Learning to optimize (L2O) is an emerging approach that leverages machine learning to
develop optimization methods, aiming at reducing the laborious iterations of hand …
develop optimization methods, aiming at reducing the laborious iterations of hand …
High Dimensional Optimization for Electronic Design
Bayesian optimization (BO) samples points of interest to update a surrogate model for a
blackbox function. This makes it a powerful technique to optimize electronic designs which …
blackbox function. This makes it a powerful technique to optimize electronic designs which …
Algorithm for Calculating the Global Minimum of a Smooth Function of Several Variables.
Z Kaidassov, ZS Tutkusheva - Mathematical Modelling of …, 2021 - search.ebscohost.com
Every year the interest of theorists and practitioners in optimisation problems is growing, and
extreme problems are found in all branches of science. Local optimisation problems are well …
extreme problems are found in all branches of science. Local optimisation problems are well …
[图书][B] Enhancing Local Derivative-Free Optimization with Curvature Information and Inspection Strategies
B Kim - 2023 - search.proquest.com
Abstract Derivative-Free Optimization (DFO) problems naturally arise in various domains,
from engineering design to hyperparameter optimization and beyond. This thesis introduces …
from engineering design to hyperparameter optimization and beyond. This thesis introduces …
A Penalty Method Based on a Gauss-Newton Scheme for AC-OPF
I Mezghani, A Papavasiliou… - 2021 IEEE Madrid …, 2021 - ieeexplore.ieee.org
We propose a globally convergent and robust GaussNewton algorithm for finding a (local)
optimal solution of a nonconvex and possibly non-smooth optimization problem arising from …
optimal solution of a nonconvex and possibly non-smooth optimization problem arising from …
A Globally Convergent Penalty-Based Gauss-Newton Algorithm with Applications
We propose a globally convergent Gauss-Newton algorithm for finding a local optimal
solution of a non-convex and possibly non-smooth optimization problem. The algorithm that …
solution of a non-convex and possibly non-smooth optimization problem. The algorithm that …