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» Anomaly Detection Using Visualization and Machine Learning
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JMLR
2006
132views more  JMLR 2006»
14 years 10 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
CLEF
2011
Springer
13 years 9 months ago
An Empirical Research: "Wikipedia Vandalism Detection using VandalSense 2.0" - Notebook for PAN at CLEF 2011
Wikipedia despite having a very small budget has been among the top ten most visited websites for over half a decade. Being this visible also generated the problem of ill intended ...
F. Gediz Aksit
ISBI
2009
IEEE
15 years 4 months ago
Lesion Detection and Segmentation in Uterine Cervix Images Using an Arc-Level MRF
This study develops a procedure for automatic extraction and segmentation of a class-specific object (or region) by learning class-specific boundaries. We present and evaluate t...
Amir Alush, Hayit Greenspan, Jacob Goldberger
WCE
2007
14 years 11 months ago
Gene Selection for Tumor Classification Using Microarray Gene Expression Data
– In this paper we perform a t-test for significant gene expression analysis in different dimensions based on molecular profiles from microarray data, and compare several computa...
Krishna Yendrapalli, Ram B. Basnet, Srinivas Mukka...
JCST
2011
89views more  JCST 2011»
14 years 5 months ago
Software Defect Detection with Rocus
Software defect detection aims to automatically identify defective software modules for efficient software test in order to improve the quality of a software system. Although many...
Yuan Jiang, Ming Li, Zhi-Hua Zhou