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JMLR
2006
132views more  JMLR 2006»
13 years 7 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
BMCBI
2004
104views more  BMCBI 2004»
13 years 7 months ago
Discriminative topological features reveal biological network mechanisms
Background: Recent genomic and bioinformatic advances have motivated the development of numerous network models intending to describe graphs of biological, technological, and soci...
Manuel Middendorf, Etay Ziv, Carter Adams, Jen Hom...
BMCBI
2006
94views more  BMCBI 2006»
13 years 7 months ago
Noise-injected neural networks show promise for use on small-sample expression data
Background: Overfitting the data is a salient issue for classifier design in small-sample settings. This is why selecting a classifier from a constrained family of classifiers, on...
Jianping Hua, James Lowey, Zixiang Xiong, Edward R...
CLEF
2010
Springer
13 years 8 months ago
ZOT! to Wikipedia Vandalism - Lab Report for PAN at CLEF 2010
Abstract This vandalism detector uses features primarily derived from a wordpreserving differencing of the text for each Wikipedia article from before and after the edit, along wit...
James White, Rebecca Maessen
ANSS
1995
IEEE
13 years 11 months ago
Algorithms for categorizing multiprocessor communication under invalidate and update-based coherence protocols
In this paper we present simulation algorithmsthat characterize the main sources of communication generated by parallel applications under both invalidate and updatebased cache co...
Ricardo Bianchini, Leonidas I. Kontothanassis