Welcome to the Convex Optimization Repository! This repository contains lab tasks and projects from my Convex Optimization class at Warsaw University.
All lab tasks from the Convex Optimization class are available in the lab folder of this repository. The original course repository is available at this link https://github.com/lkowalik/ConvexOptimization2024.
In addition to the lab tasks, you will find four homework assignments in this repository.
This repository is organized as follows:
- lab/: Contains lab tasks completed during classes.
- homework1: Theoretical task - proving the concavity of a function.
- homework2: Programming task "Max-Probability-of-Loss" from the "Additional Exercises" collection for the Convex Optimization textbook by S. Boyd and L. Vandenberghe.
- homework3: Programming task "Learning a Quadratic Pseudo-Metric from Distance Measurements" from the Convex Optimization textbook by S. Boyd and L. Vandenberghe.
- homework4: Implementation of Gradient Descent and Newton's Method for a given unconstrained problem from the Convex Optimization textbook by S. Boyd and L. Vandenberghe.