56 search results - page 1 / 12 » Approximation of Data by Decomposable Belief Models |
IPMU
2010
Springer
13 years 3 months ago
2010
Springer
It is well known that among all probabilistic graphical Markov models the class of decomposable models is the most advantageous in the sense that the respective distributions can b...
IAT
2005
IEEE
13 years 10 months ago
2005
IEEE
Partially observable Markov decision process (POMDP) is commonly used to model a stochastic environment with unobservable states for supporting optimal decision making. Computing ...
WABI
2007
Springer
13 years 10 months ago
2007
Springer
Abstract. Parameter estimation of large bio-pathway models is an important and difficult problem. To reduce the prohibitive computational cost, one approach is to decompose a large...
JMLR
2006
13 years 4 months ago
2006
We present a new framework based on walks in a graph for analysis and inference in Gaussian graphical models. The key idea is to decompose the correlation between each pair of var...
CIKM
2010
Springer
13 years 3 months ago
2010
Springer
Low-dimensional topic models have been proven very useful for modeling a large corpus of documents that share a relatively small number of topics. Dimensionality reduction tools s...