There are 0 repository under unconstrained-optimization topic.
Optimization functions for Julia
LBFGS-Lite: A header-only L-BFGS unconstrained optimizer.
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.
Optimization algorithms by M.J.D. Powell
Solve a max-cut problem using a quantum computer
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)"
Perform basic image segmentation using discrete quadratic models (DQM) and hybrid solvers.
Optimizers for/and sklearn compatible Machine Learning models
Optimization algorithms written in Python and MATLAB
numerical optimization subroutines in Fortran generated by ChatGPT-4
Optimization course assignments under the supervision of Dr. Maryam Amirmazlaghani
Benchmarking optimization solvers.
A CUTEst practical installer
CG_DESCENT unconstrained nonlinear optimization algorithm by William W. Hager and Hongchao Zhang in single header library, original code taken from http://users.clas.ufl.edu/hager/papers/Software/
Implementation of collection of test functions for UO(Unconstrained Optimization)
rosenbrock function optimization with four different methods (unconstrained optimization)
A repository of optimization algorithms implemented in Python & MATLAB for mathematical optimization problems. Algorithms such as Genetic Algorithm, PSO, linear programming, and etc.
This repository contains assignments completed in the course "Convex Optimisation" using python
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.
Some numerical optimization method in Python
PRIMA: Reference Implementation for Powell's methods with Modernization and Amelioration
Provided a function (written in natural mathematical notation), returns a maxima or minima.
Estimating the 2-norm for a rectangular matrix (unconstrained approach) using two optimization algorithms: Standard gradient descent (steepest descent) method, and quasi-Newton method
Algorithms in Statistical Machine Learning and Data Mining
Course Projects for Operations Research in USTC (2021 Fall).
A Python package integrating around ten unconstrained optimization algorithms, inclusive of 2D/3D visualizations for comparative analysis, and incorporated matrix operations.
A set of Jupyter notebooks that investigate and compare the performance of several numerical optimization techniques, both unconstrained (univariate search, Powell's method and Gradient Descent (fixed step and optimal step)) and constrained (Exterior Penalty method).
Assignments in unconstrained optimization course covering 1st half of Nocedal and Wright textbook.