2278 search results - page 27 / 456 » Markov logic networks |
SODA
2001
ACM
13 years 9 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 ...
AMC
2008
13 years 7 months ago
2008
In this paper, a general framework for the analysis of a connection between the training of artificial neural networks via the dynamics of Markov chains and the approximation of c...
CORR
2012
Springer
12 years 3 months ago
2012
Springer
Markov jump processes and continuous time Bayesian networks are important classes of continuous time dynamical systems. In this paper, we tackle the problem of inferring unobserve...
ICALP
2009
Springer
14 years 8 months ago
2009
Springer
We take a dual view of Markov processes ? advocated by Kozen ? as transformers of bounded measurable functions. We redevelop the theory of labelled Markov processes from this view ...
GECCO
2007
Springer
14 years 1 months ago
2007
Springer
Markov Networks (also known as Markov Random Fields) have been proposed as a new approach to probabilistic modelling in Estimation of Distribution Algorithms (EDAs). An EDA employ...