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ICML
1996
IEEE
16 years 7 months ago
Discretizing Continuous Attributes While Learning Bayesian Networks
We introduce a method for learning Bayesian networks that handles the discretization of continuous variables as an integral part of the learning process. The main ingredient in th...
Moisés Goldszmidt, Nir Friedman
ISMIS
2005
Springer
16 years 7 days ago
Robust Inference of Bayesian Networks Using Speciated Evolution and Ensemble
Recently, there are many researchers to design Bayesian network structures using evolutionary algorithms but most of them use the only one fittest solution in the last generation. ...
Kyung-Joong Kim, Ji-Oh Yoo, Sung-Bae Cho
ADVCS
2011
251views Database» more  ADVCS 2011»
14 years 6 months ago
Emergent Social Learning Networks in Organizations with Heterogeneous Agents
Two distinct learning mechanisms are considered for a population of agents who engage in decentralized search for the common optimum. An agent may choose to learn via innovation (...
Myong-Hun Chang
ACMSE
2008
ACM
15 years 8 months ago
A distributed firewall and active response architecture providing preemptive protection
Firewalls provide very good network security features. However, classical perimeter firewall deployments suffer from limitations due to complex network topologies and the inabilit...
J. Lane Thames, Randal Abler, David Keeling
COMCOM
2006
151views more  COMCOM 2006»
15 years 6 months ago
Characteristic analysis of internet traffic from the perspective of flows
The necessity of network traffic monitoring and analysis is growing dramatically with increasing network usage demands from individual users as well as business communities. Most ...
Myung-Sup Kim, Young J. Won, James W. Hong