319 search results - page 2 / 64 » Learning Equivalence Classes of Bayesian Network Structures |
UAI
1998
13 years 6 months ago
1998
In recent years there has been a flurry of works on learning Bayesian networks from data. One of the hard problems in this area is how to effectively learn the structure of a beli...
ML
2006
ACM
13 years 5 months ago
2006
ACM
We present a new algorithm for Bayesian network structure learning, called Max-Min Hill-Climbing (MMHC). The algorithm combines ideas from local learning, constraint-based, and sea...
AI
2002
Springer
13 years 5 months ago
2002
Springer
Bayesian networks, equivalently graphical Markov models determined by acyclic digraphs or ADGs (also called directed acyclic graphs or dags), have proved to be both effective and ...
JMLR
2002
13 years 5 months ago
2002
In this paper we prove the so-called "Meek Conjecture". In particular, we show that if a DAG H is an independence map of another DAG G, then there exists a finite sequen...
IJAR
2010
13 years 3 months ago
2010
We recall the basic idea of an algebraic approach to learning Bayesian network (BN) structures, namely to represent every BN structure by a certain (uniquely determined) vector, c...