GSoC/GCI Archive
Google Summer of Code 2013 Shogun Machine Learning Toolbox

Implement algorithms for Blind Source Separation (BSS) and Independent Component Analysis (ICA) based on Approximate Joint Diagonalization (AJD) of matrices.

by Kevin for Shogun Machine Learning Toolbox

ICA/BSS can be done via the approximate joint diagonalization (AJD) of matrices. ADJ is the problem of finding a matrix, or set of basis vectors, that best diagonalizes a set of input matrices. It is an important tool playing a critical role in many applications including ICA and BSS. For machine learning in particular ICA can be used for pre-processing, automatic feature selection and dimensionality reduction for visualization. ADJ would be a valuable addition to the SHOGUN toolbox.