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AI
2006
Springer
13 years 7 months ago
Controlled generation of hard and easy Bayesian networks: Impact on maximal clique size in tree clustering
This article presents and analyzes algorithms that systematically generate random Bayesian networks of varying difficulty levels, with respect to inference using tree clustering. ...
Ole J. Mengshoel, David C. Wilkins, Dan Roth
ICML
2009
IEEE
14 years 8 months ago
Structure learning of Bayesian networks using constraints
This paper addresses exact learning of Bayesian network structure from data and expert's knowledge based on score functions that are decomposable. First, it describes useful ...
Cassio Polpo de Campos, Zhi Zeng, Qiang Ji
ICNC
2005
Springer
14 years 1 months ago
Applying Genetic Programming to Evolve Learned Rules for Network Anomaly Detection
The DARPA/MIT Lincoln Laboratory off-line intrusion detection evaluation data set is the most widely used public benchmark for testing intrusion detection systems. But the presence...
Chuanhuan Yin, Shengfeng Tian, Houkuan Huang, Jun ...
ICPR
2008
IEEE
14 years 8 months ago
Exploiting qualitative domain knowledge for learning Bayesian network parameters with incomplete data
When a large amount of data are missing, or when multiple hidden nodes exist, learning parameters in Bayesian networks (BNs) becomes extremely difficult. This paper presents a lea...
Qiang Ji, Wenhui Liao
ASC
2004
13 years 7 months ago
Clustering terms in the Bayesian network retrieval model: a new approach with two term-layers
The retrieval performance of an information retrieval system usually increases when it uses the relationships among the terms contained in a given document collection. However, th...
Luis M. de Campos, Juan M. Fernández-Luna, ...