Simplifying mixture models through function approximation.
Published in IEEE transactions on neural networks • Feb 22, 2010
NobleIDNI7P68W03R75S64
Authors:,
Kwok JT
Zhang K
Abstract
The finite mixture model is widely used in various statistical learning problems. However, the model obtained may contain a large number of components, making it inefficient in practical applications. In this paper, we propose to simplify the mixture model by minimizing an upper bound of the approxi...
Finding related papers...
Discussions
(0)No comments yet
Be the first to share your thoughts!