Part of Advances in Neural Information Processing Systems 15 (NIPS 2002)
Kenji Fukumizu, Shotaro Akaho, Shun-ichi Amari
We show the existence of critical points as lines for the likelihood func- tion of mixture-type models. They are given by embedding of a critical point for models with less components. A sufﬁcient condition that the critical line gives local maxima or saddle points is also derived. Based on this fact, a component-split method is proposed for a mixture of Gaus- sian components, and its effectiveness is veriﬁed through experiments.