142 search results - page 12 / 29 » Bayesian variable order Markov models. |
ICA
2007
Springer
13 years 11 months ago
2007
Springer
In modelling nonstationary sources, one possible strategy is to define a latent process of strictly positive variables to model variations in second order statistics of the underly...
NIPS
2007
13 years 9 months ago
2007
Bayesian Reinforcement Learning has generated substantial interest recently, as it provides an elegant solution to the exploration-exploitation trade-off in reinforcement learning...
JETAI
1998
13 years 7 months ago
1998
Graphical structures such as Bayesian networks or Markov networks are very useful tools for representing irrelevance or independency relationships, and they may be used to e cientl...
AAAI
2008
13 years 10 months ago
2008
Markov logic networks (MLNs) combine first-order logic and Markov networks, allowing us to handle the complexity and uncertainty of real-world problems in a single consistent fram...
KDD
2009
ACM
14 years 8 months ago
2009
ACM
Learning probabilistic graphical models from high-dimensional datasets is a computationally challenging task. In many interesting applications, the domain dimensionality is such a...