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AI
2002
Springer
15 years 6 months ago
Learning Bayesian networks from data: An information-theory based approach
This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
Jie Cheng, Russell Greiner, Jonathan Kelly, David ...
ASC
2004
15 years 6 months ago
Soft computing applications in dynamic model identification of polymer extrusion process
This paper proposes the applications of soft computing to deal with the constraints in conventional modelling techniques of the dynamic extrusion process. The proposed technique i...
Leong Ping Tan, Ahmad Lotfi, Eugene Lai, J. B. Hul...
CORR
2004
Springer
218views Education» more  CORR 2004»
15 years 6 months ago
A Dynamic Clustering-Based Markov Model for Web Usage Mining
Markov models have been widely utilized for modelling user web navigation behaviour. In this work we propose a dynamic clustering-based method to increase a Markov model's ac...
José Borges, Mark Levene
SIAMJO
2000
101views more  SIAMJO 2000»
15 years 6 months ago
An Efficient Algorithm for Minimizing a Sum of p-Norms
We study the problem of minimizing a sum of p-norms where p is a fixed real number in the interval [1, ]. Several practical algorithms have been proposed to solve this problem. How...
Guoliang Xue, Yinyu Ye
INFORMATICALT
2002
91views more  INFORMATICALT 2002»
15 years 6 months ago
Bayesian Heuristic Approach to Scheduling
Abstract. Real life scheduling problems are solved by heuristics with parameters defined by experts, as usual. In this paper a new approach is proposed where the parameters of vari...
Jonas Mockus