project-optim

Homework for the course Optimization theory with applications

📅 Date: Dec 2019

🏫 Master in Data Science and Engineering at EURECOM

Description

Homework 1

Convex sets and functions

Assignment: here
My solution: done on paper

Homework 2

Implementation of gradient descent and dual ascent

Assignment: here
My solution: exercise 1: hmw2_1.ipynb, exercise 2: hmw2_2.ipynb

Run the code

To run the code, you need Python 3, Jupyter Notebook (or JupyterLab) and the Python packages listed in requirements.txt.

Using virtual environment

Create a virtual environment, install the package dependencies and add a custom kernel to Jupyter:

$ python -m venv venv
$ source venv/bin/activate
(venv) $ pip install -r requirements.txt ipykernel
(venv) $ ipython kernel install --user --name=project-optim
(venv) $ deactivate

Now you can simply run:

$ jupyter-lab

and open the two notebook files.

License

The source code is licensed under the GNU GPLv3. The content of the report is licensed under the CC BY-NC-SA 4.0