95 search results - page 11 / 19 » Learning Non-Stationary Dynamic Bayesian Networks |
NECO
2002
13 years 8 months ago
2002
A Bayesian ensemble learning method is introduced for unsupervised extraction of dynamic processes from noisy data. The data are assumed to be generated by an unknown nonlinear ma...
ICML
2009
IEEE
14 years 9 months ago
2009
IEEE
Relational world models that can be learned from experience in stochastic domains have received significant attention recently. However, efficient planning using these models rema...
ICML
2000
IEEE
14 years 9 months ago
2000
IEEE
We consider the problem of unsupervised classification of temporal sequences of facial expressions in video. This problem arises in the design of an adaptive visual agent, which m...
ICDM
2009
IEEE
14 years 3 months ago
2009
IEEE
—Mining temporal network models from discrete event streams is an important problem with applications in computational neuroscience, physical plant diagnostics, and human-compute...
NIPS
2000
13 years 10 months ago
2000
The human figure exhibits complex and rich dynamic behavior that is both nonlinear and time-varying. Effective models of human dynamics can be learned from motion capture data usi...