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103
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ADMA
2006
Springer
110views Data Mining» more  ADMA 2006»
15 years 6 months ago
Learning with Local Drift Detection
Abstract. Most of the work in Machine Learning assume that examples are generated at random according to some stationary probability distribution. In this work we study the problem...
João Gama, Gladys Castillo
127
Voted
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
148
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IJNSEC
2010
141views more  IJNSEC 2010»
14 years 9 months ago
Protection of an Intrusion Detection Engine with Watermarking in Ad Hoc Networks
In this paper we present an intrusion detection engine comprised of two main elements; firstly, a neural network for the actual detection task and secondly watermarking techniques...
Aikaterini Mitrokotsa, Nikos Komninos, Christos Do...
150
Voted
CLEF
2011
Springer
14 years 2 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
134
Voted
WCE
2007
15 years 3 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...