71 search results - page 10 / 15 » A Causal Bayesian Network View of Reinforcement Learning |
APIN
1999
14 years 9 months ago
1999
We present a method for mapping a given Bayesian network to a Boltzmann machine architecture, in the sense that the the updating process of the resulting Boltzmann machine model pr...
NIPS
1997
14 years 11 months ago
1997
We address the problem of learning structure in nonlinear Markov networks with continuous variables. This can be viewed as non-Gaussian multidimensional density estimation exploit...
78
Voted
PKDD
2009
Springer
15 years 4 months ago
2009
Springer
Probabilistic logics have attracted a great deal of attention during the past few years. While logical languages have taken a central position in research on knowledge representati...
IJAR
2011
14 years 1 months ago
2011
The basic idea of an algebraic approach to learning Bayesian network (BN) structures is to represent every BN structure by a certain uniquely determined vector, called the standar...
ICA
2010
Springer
14 years 10 months ago
2010
Springer
Abstract. We discuss causal structure learning based on linear structural equation models. Conventional learning methods most often assume Gaussianity and create many indistinguish...