Unconstrained optimization algorithms in python, line search and trust region methods
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Updated
Dec 19, 2018 - Jupyter Notebook
Unconstrained optimization algorithms in python, line search and trust region methods
A Matlab/Octave package for oscillatory integration
A Unified Pytorch Optimizer for Numerical Optimization
This contains three programs written in python. Gauss-Seidel and Successive Over Relaxation to solve system of equations and Steepest-Descent to minimize a function of 2 or 3 variables.
Computational methods for beam angle optimization in intensity modulated radiotherapy
Project for the Numerical Linear Algebra course @{cse.uoi.gr, math.uoi.gr}
Implementation of Unconstrained minimization algorithms. These are listed below:
Implementation of our paper entitiled FAMINet: Learning Real-time Semi-supervised Video Object Segmentation with Steepest Optimized Optical Flow published in TIM.
Implementation of unconstrained optimization techniques in Matlab
A matlab function for steepest descent optimization using Quasi Newton's method : BGFS & DFP
This repository consists of Lab Assignments for course Machine Learning.
Pseudo-Inverse, Gradient-Stochastic-Steepest Descent, Logistic Regression and LDA-QDA
Analytical and Numerical Approximation of functions
Fortran/Python linear algebra utilities
This repository will comprise primary optimization algorithms in Python language. Optimization is an extremely important part of machine learning.
A fun side project to perform AI algorithms using plain java code.
Steepest Descent Method is studied for Rosenbrock function.
Gradient descent approximation of orthogonal projection of a point on a convex periodic curve
Through this project we will try to understand working of Steepest-Descent and Gradient-Descent method and the differences between them.
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