440 search results - page 1 / 88 » Learning Nonlinear Dynamic Models from Non-sequenced Data |
JMLR
2010
12 years 11 months ago
2010
Virtually all methods of learning dynamic systems from data start from the same basic assumption: the learning algorithm will be given a sequence of data generated from the dynami...
NECO
2002
13 years 4 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
2006
IEEE
14 years 5 months ago
2006
IEEE
The recent Predictive Linear Gaussian model (or PLG) improves upon traditional linear dynamical system models by using a predictive representation of state, which makes consistent...
PAMI
2008
13 years 4 months ago
2008
We introduce Gaussian process dynamical models (GPDMs) for nonlinear time series analysis, with applications to learning models of human pose and motion from high-dimensional motio...
NIPS
1998
13 years 6 months ago
1998
The Expectation Maximization EM algorithm is an iterative procedure for maximum likelihood parameter estimation from data sets with missing or hidden variables 2 . It has been app...