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» Anomaly Detection Through a Bayesian Support Vector Machine
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ICC
2007
IEEE
132views Communications» more  ICC 2007»
14 years 2 months ago
Quarter Sphere Based Distributed Anomaly Detection in Wireless Sensor Networks
—Anomaly detection is an important challenge for tasks such as fault diagnosis and intrusion detection in energy constrained wireless sensor networks. A key problem is how to min...
Sutharshan Rajasegarar, Christopher Leckie, Marimu...
GECCO
2005
Springer
126views Optimization» more  GECCO 2005»
14 years 2 months ago
Is negative selection appropriate for anomaly detection?
Negative selection algorithms for hamming and real-valued shape-spaces are reviewed. Problems are identified with the use of these shape-spaces, and the negative selection algori...
Thomas Stibor, Philipp H. Mohr, Jonathan Timmis, C...
ICMLA
2010
13 years 6 months ago
Semi-Supervised Anomaly Detection for EEG Waveforms Using Deep Belief Nets
Abstract--Clinical electroencephalography (EEG) is routinely used to monitor brain function in critically ill patients, and specific EEG waveforms are recognized by clinicians as s...
Drausin Wulsin, Justin Blanco, Ram Mani, Brian Lit...
JCB
2006
138views more  JCB 2006»
13 years 8 months ago
Recognition and Classification of Histones Using Support Vector Machine
Histones are DNA-binding proteins found in the chromatin of all eukaryotic cells. They are highly conserved and can be grouped into five major classes: H1/H5, H2A, H2B, H3, and H4...
Manoj Bhasin, Ellis L. Reinherz, Pedro A. Reche
BMCBI
2010
88views more  BMCBI 2010»
13 years 8 months ago
Proteome scanning to predict PDZ domain interactions using support vector machines
Background: PDZ domains mediate protein-protein interactions involved in important biological processes through the recognition of short linear motifs in their target proteins. Tw...
Shirley Hui, Gary D. Bader