The following lecture talks about the Markowitz Portfolio Optimization problem in convex optimization. Indeed, many variants of this problem exists, but the classical one looks like this where is an sized vector containing the amount of assets to invest in. The vector is the mean of the relative […]

📚About This lecture focuses on the theoretical as well as practical aspects of the Support Vector Machines. It is a supervised learning model associated with learning algorithms that analyze data used for classification and regression analysis. Developed at AT&T Bell Laboratories by Vapnik with colleagues (Boser et al., 1992, Guyon […]

This tutorial is brought to you by DataCamp. The tutorial does the most in rigorously explaining the little bits and pieces of the wonderful Matplotlib. Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. Matplotlib makes easy things easy and hard things easier. Contents of […]

In this lecture, we talk about equivalent reformulations, that are reformulations done on the initial problem of the form (1) A very interesting question is the following. Assume we got two problems and that are equivalent problems. Are their duals, (hereby denoted by and , respectively) the same ? […]

In a previous post of mine, I talked about CVXOPT Programming. In this one, we’ll introduce cone programming. So first things first. Cone programming is a term (short for second-order cone program (SOCP)) is a convex optimization problem of the following form (1) where matrices fall in and vectors . On the […]