30 search results - page 5 / 6 » Probabilistic Inference for Fast Learning in Control |
NIPS
2004
13 years 7 months ago
2004
Directed graphical models with one layer of observed random variables and one or more layers of hidden random variables have been the dominant modelling paradigm in many research ...
CVPR
2010
IEEE
13 years 10 months ago
2010
IEEE
Long-term persistent tracking in ever-changing environments is a challenging task, which often requires addressing difficult object appearance update problems. To solve them, most...
CORR
2012
Springer
12 years 1 months ago
2012
Springer
We present sparse topical coding (STC), a non-probabilistic formulation of topic models for discovering latent representations of large collections of data. Unlike probabilistic t...
JNCA
2011
13 years 14 days ago
2011
Popular Internet applications deploy a multi-tier architecture, with each tier provisioning a certain functionality to its preceding tier. In this paper, we address the challengin...
NN
1997
Springer
13 years 9 months ago
1997
Springer
Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...