Title: On the Estimation of Entropy in the FastICA Algorithm,
Abstract: The fastICA algorithm is a popular dimension reduction technique used to
reveal patterns in data. Here we show that the approximations used in fastICA
can result in patterns not being successfully recognised. We demonstrate this
problem using a two-dimensional example where a clear structure is immediately
visible to the naked eye, but where the projection chosen by fastICA fails to
reveal this structure. This implies that care is needed when applying fastICA.
We discuss how the problem arises and how it is intrinsically connected to the
approximations that form the basis of the computational efficiency of fastICA.