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JMLR
2006
132views more  JMLR 2006»
15 years 2 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
140
Voted
WWW
2002
ACM
16 years 3 months ago
Using web structure for classifying and describing web pages
The structure of the web is increasingly being used to improve organization, search, and analysis of information on the web. For example, Google uses the text in citing documents ...
Eric J. Glover, Kostas Tsioutsiouliklis, Steve Law...
KDD
2010
ACM
272views Data Mining» more  KDD 2010»
15 years 6 months ago
Beyond heuristics: learning to classify vulnerabilities and predict exploits
The security demands on modern system administration are enormous and getting worse. Chief among these demands, administrators must monitor the continual ongoing disclosure of sof...
Mehran Bozorgi, Lawrence K. Saul, Stefan Savage, G...
138
Voted
CVPR
2008
IEEE
16 years 4 months ago
Unifying discriminative visual codebook generation with classifier training for object category recognition
The idea of representing images using a bag of visual words is currently popular in object category recognition. Since this representation is typically constructed using unsupervi...
Liu Yang, Rong Jin, Rahul Sukthankar, Fréd&...
156
Voted
KDD
2003
ACM
180views Data Mining» more  KDD 2003»
16 years 3 months ago
Classifying large data sets using SVMs with hierarchical clusters
Support vector machines (SVMs) have been promising methods for classification and regression analysis because of their solid mathematical foundations which convey several salient ...
Hwanjo Yu, Jiong Yang, Jiawei Han