This repository contains the projects I completed for the Distributed Optimization and Learning course at Tehran University.
Getting Started
- This repository assumes you have Python and libraries for Deep Learning, such as Pytorch.
Contents
This repository includes folders for each project. Each folder will likely contain:
- Jupyter notebooks or Python scripts implementing the project.
- Data files used for training and testing (if applicable).
- README.md file (optional, for project-specific details).
Project Descriptions
1. Decentralized Optimization: Primal and Dual Decomposition in Federated Setting
This project explored decentralized optimization algorithms for training a deep learning model in federated settings.
2. Distributed Optimization: Weighted Average Algorithm
This project focused on distributed optimization algorithms for training deep learning models across multiple machines without a coordinator server.