Optimization functions for Julia
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Updated
Jun 1, 2024 - Julia
Optimization functions for Julia
LBFGS-Lite: A header-only L-BFGS unconstrained optimizer.
A collection of Benchmark functions for numerical optimization problems
PRIMA is a package for solving general nonlinear optimization problems without using derivatives. It provides the reference implementation for Powell's derivative-free optimization methods, i.e., COBYLA, UOBYQA, NEWUOA, BOBYQA, and LINCOA. PRIMA means Reference Implementation for Powell's methods with Modernization and Amelioration, P for Powell.
Solve a max-cut problem using a quantum computer
Powell's Derivative-Free Optimization solvers.
The Constrained and Unconstrained Testing Environment with safe threads (CUTEst) for optimization software
Perform basic image segmentation using discrete quadratic models (DQM) and hybrid solvers.
Optimization algorithms by M.J.D. Powell
Unconstrained optimization algorithms in python, line search and trust region methods
This repository contains the code and models for our paper "Investigating and Mitigating Failure Modes in Physics-informed Neural Networks(PINNs)"
Optimization course assignments under the supervision of Dr. Maryam Amirmazlaghani
Optimizers for/and sklearn compatible Machine Learning models
Optimization algorithms written in Python and MATLAB
An optimization solver for unconstrained differentiable problems
PRIMA: Reference Implementation for Powell's methods with Modernization and Amelioration
Computational Mathematics (CM) for learning and data analysis Project - Training a neural network with nonlinear conjugate gradient (FR, PR, HS, PR+, HS+) and limited-memory bfgs methods.
optimization techniques for data mining
Benchmarking optimization solvers.
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