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» Network Intrusion Detection Using Genetic Clustering
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GECCO
2004
Springer
116views Optimization» more  GECCO 2004»
14 years 3 months ago
Reducing Fitness Evaluations Using Clustering Techniques and Neural Network Ensembles
Abstract. In many real-world applications of evolutionary computation, it is essential to reduce the number of fitness evaluations. To this end, computationally efficient models c...
Yaochu Jin, Bernhard Sendhoff
BMCBI
2010
214views more  BMCBI 2010»
13 years 10 months ago
AutoSOME: a clustering method for identifying gene expression modules without prior knowledge of cluster number
Background: Clustering the information content of large high-dimensional gene expression datasets has widespread application in "omics" biology. Unfortunately, the under...
Aaron M. Newman, James B. Cooper
ICCS
2007
Springer
14 years 4 months ago
DDDAS/ITR: A Data Mining and Exploration Middleware for Grid and Distributed Computing
We describe our project that marries data mining together with Grid computing. Specifically, we focus on one data mining application - the Minnesota Intrusion Detection System (MIN...
Jon B. Weissman, Vipin Kumar, Varun Chandola, Eric...
ACMSE
2005
ACM
13 years 12 months ago
Simulating application level self-similar network traffic using hybrid heavy-tailed distributions
Many networking researches depend on an accurate simulation of network traffic. For example, Intrusion Detection Systems generally require tuning to be effective in each new envir...
Song Luo, Gerald A. Marin
ICPP
2005
IEEE
14 years 3 months ago
Push-Pull: Guided Search DAG Scheduling for Heterogeneous Clusters
Consider a heterogeneous cluster system, consisting of processors with varying processing capabilities and network links with varying bandwidths. Given a DAG application to be sch...
Sang Cheol Kim, Sunggu Lee