# First thoughts on Orthogonal Matching Pursuit

I am working on implementing the Orthogonal Matching Pursuit (OMP) algorithm for the scikit. It is an elegant algorithm (that almost writes itself in Numpy!) to compute a greedy approximation to the solution of a sparse coding problem:

\$\$ \text{argmin} \big|\big|\gamma\big|\big|_0 \text{ subject to }\big …

# Sparse PCA

I have been working on the integration into the scikits.learn codebase of a sparse principal components analysis (SparsePCA) algorithm coded by Gaël and Alexandre and based on [[1]][]. Because the name “sparse PCA” has some inherent ambiguity, I will describe in greater depth what problem we are actually solving …

# An overview of dictionary learning: Terminology

My GSoC proposal is titled “Dictionary learning in scikits.learn” and in the project, I plan to implement methods used in state of the art research and industry applications in signal and image processing. In this post, I want to clarify the terminology used.

Usually the terms dictionary learning and …