This paper addresses the problem of automatically acquiring context models from data. Context and human behavior are represented using a state model, called situation model. This ...
James L. Crowley, Oliver Brdiczka, Patrick Reignie...
Gaussian Process prior models, as used in Bayesian non-parametric statistical models methodology are applied to implement a nonlinear adaptive control law. The expected value of a...
The high speed at which new businesses are developed can to a large extent be attributed to their ability to flexibly combine existing services into an integrated business platfor...
We address the problem of learning topic hierarchies from data. The model selection problem in this domain is daunting—which of the large collection of possible trees to use? We...
David M. Blei, Thomas L. Griffiths, Michael I. Jor...
Using a nonlinear 15-state helicopter model in 6 DOF, two di erent neural control systems, both acting as rate damping, have been designed and compared. They are both based on the ...