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JMLR
2006
132views more  JMLR 2006»
13 years 9 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
EVOW
2006
Springer
14 years 22 days ago
Functional Classification of G-Protein Coupled Receptors, Based on Their Specific Ligand Coupling Patterns
Functional identification of G-Protein Coupled Receptors (GPCRs) is one of the current focus areas of pharmaceutical research. Although thousands of GPCR sequences are known, many ...
Burcu Bakir, Osman Ugur Sezerman
WWW
2008
ACM
14 years 9 months ago
Learning transportation mode from raw gps data for geographic applications on the web
Geographic information has spawned many novel Web applications where global positioning system (GPS) plays important roles in bridging the applications and end users. Learning kno...
Yu Zheng, Like Liu, Longhao Wang, Xing Xie
ECML
2007
Springer
14 years 3 months ago
Principal Component Analysis for Large Scale Problems with Lots of Missing Values
Abstract. Principal component analysis (PCA) is a well-known classical data analysis technique. There are a number of algorithms for solving the problem, some scaling better than o...
Tapani Raiko, Alexander Ilin, Juha Karhunen
DAGM
2004
Springer
14 years 2 months ago
Learning from Labeled and Unlabeled Data Using Random Walks
We consider the general problem of learning from labeled and unlabeled data. Given a set of points, some of them are labeled, and the remaining points are unlabeled. The goal is to...
Dengyong Zhou, Bernhard Schölkopf