204 search results - page 34 / 41 » Proposition-valued random variables as information |
SODA
2001
ACM
13 years 8 months ago
2001
ACM
Markov networks are a common class of graphical models used in machine learning. Such models use an undirected graph to capture dependency information among random variables in a ...
UAI
2004
13 years 8 months ago
2004
We present new MCMC algorithms for computing the posterior distributions and expectations of the unknown variables in undirected graphical models with regular structure. For demon...
UAI
2004
13 years 8 months ago
2004
We show that the class of strongly connected graphical models with treewidth at most k can be properly efficiently PAC-learnt with respect to the Kullback-Leibler Divergence. Prev...
FSKD
2008
Springer
13 years 8 months ago
2008
Springer
Support Vector Machine (SVM) has been widely studied and shown success in many application fields. However, the performance of SVM drops significantly when it is applied to the pr...
FTML
2008
13 years 7 months ago
2008
The formalism of probabilistic graphical models provides a unifying framework for capturing complex dependencies among random variables, and building large-scale multivariate stat...