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JMLR
2006
132views more  JMLR 2006»
14 years 11 months ago
Learning to Detect and Classify Malicious Executables in the Wild
We describe the use of machine learning and data mining to detect and classify malicious executables as they appear in the wild. We gathered 1,971 benign and 1,651 malicious execu...
Jeremy Z. Kolter, Marcus A. Maloof
ENC
2004
IEEE
15 years 3 months ago
Distributed Learning in Intentional BDI Multi-Agent Systems
Despite the relevance of the belief-desire-intention (BDI) model of rational agency, little work has been done to deal with its two main limitations: the lack of learning competen...
Alejandro Guerra-Hernández, Amal El Fallah-...
WWW
2008
ACM
16 years 8 days ago
Enhanced hierarchical classification via isotonic smoothing
Hierarchical topic taxonomies have proliferated on the World Wide Web [5, 18], and exploiting the output space decompositions they induce in automated classification systems is an...
Kunal Punera, Joydeep Ghosh
ICMLA
2007
15 years 1 months ago
Estimating class probabilities in random forests
For both single probability estimation trees (PETs) and ensembles of such trees, commonly employed class probability estimates correct the observed relative class frequencies in e...
Henrik Boström
ML
2002
ACM
135views Machine Learning» more  ML 2002»
14 years 11 months ago
Bayesian Treed Models
When simple parametric models such as linear regression fail to adequately approximate a relationship across an entire set of data, an alternative may be to consider a partition o...
Hugh A. Chipman, Edward I. George, Robert E. McCul...