31 search results - page 2 / 7 » Learning Markov Network Structure using Few Independence Tes... |
ICML
2010
IEEE
13 years 6 months ago
2010
IEEE
The structure of a Markov network is typically learned using top-down search. At each step, the search specializes a feature by conjoining it to the variable or feature that most ...
GECCO
2009
Springer
13 years 9 months ago
2009
Springer
We propose a cooperative-coevolution – Parisian trend – algorithm, IMPEA (Independence Model based Parisian EA), to the problem of Bayesian networks structure estimation. It i...
JETAI
1998
13 years 4 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...
ICML
2009
IEEE
14 years 5 months ago
2009
IEEE
Standard inductive learning requires that training and test instances come from the same distribution. Transfer learning seeks to remove this restriction. In shallow transfer, tes...
AIME
2007
Springer
13 years 9 months ago
2007
Springer
Abstract. Disease processes in patients are temporal in nature and involve uncertainty. It is necessary to gain insight into these processes when aiming at improving the diagnosis,...