Learning Multi-Class Dynamics
Blake, Andrew, North, Ben, Isard, Michael
–Neural Information Processing Systems
Yule-Walker) are available for learning Auto-Regressive process models of simple, directly observable, dynamical processes.When sensor noise means that dynamics are observed only approximately, learning can still been achieved via Expectation-Maximisation (EM) together with Kalman Filtering. However, this does not handle more complex dynamics, involving multiple classes of motion.
Neural Information Processing Systems
Dec-31-1999