Part of Advances in Neural Information Processing Systems 15 (NIPS 2002)
Trevor Hastie, Rob Tibshirani
We present a simple direct approach for solving the ICA problem, using density estimation and maximum likelihood. Given a candi(cid:173) date orthogonal frame, we model each of the coordinates using a semi-parametric density estimate based on cubic splines. Since our estimates have two continuous derivatives, we can easily run a sec(cid:173) ond order search for the frame parameters. Our method performs very favorably when compared to state-of-the-art techniques.