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
Implementation of approximate free-energy minimization in PyTorch
A Matlab/Octave package for oscillatory integration
Implementation of our paper entitiled FAMINet: Learning Real-time Semi-supervised Video Object Segmentation with Steepest Optimized Optical Flow published in TIM.
A matlab function for steepest descent optimization using Quasi Newton's method : BGFS & DFP
A Unified Pytorch Optimizer for Numerical Optimization
Implementation of unconstrained optimization techniques in Matlab
[NeurIPS2024 (Spotlight)] "Unified Gradient-Based Machine Unlearning with Remain Geometry Enhancement" by Zhehao Huang, Xinwen Cheng, JingHao Zheng, Haoran Wang, Zhengbao He, Tao Li, Xiaolin Huang
Fortran/Python linear algebra utilities
Demonstration of gradient descent methods
Implementations of various Algorithms used in Numerical Analysis, from root-finding up to gradient descent and numerically solving PDEs.
Implementation of Unconstrained minimization algorithms. These are listed below:
This repository consists of Lab Assignments for course Machine Learning.
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.
Pseudo-Inverse, Gradient-Stochastic-Steepest Descent, Logistic Regression and LDA-QDA
Contains a mathematical optimization project implemented in Python
The implementation of advanced mathematical optimization methods
Numerical optimization algorithms with examples in Python.
Example Code for numerical optimization. Written in python.
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