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» Using Active Learning in Intrusion Detection
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KDD
2003
ACM
148views Data Mining» more  KDD 2003»
15 years 11 months ago
Mining concept-drifting data streams using ensemble classifiers
Recently, mining data streams with concept drifts for actionable insights has become an important and challenging task for a wide range of applications including credit card fraud...
Haixun Wang, Wei Fan, Philip S. Yu, Jiawei Han
AGI
2011
14 years 2 months ago
Imprecise Probability as a Linking Mechanism between Deep Learning, Symbolic Cognition and Local Feature Detection in Vision Pro
A novel approach to computer vision is outlined, involving the use of imprecise probabilities to connect a deep learning based hierarchical vision system with both local feature de...
Ben Goertzel
BMCBI
2008
143views more  BMCBI 2008»
14 years 10 months ago
Automatic detection of exonic splicing enhancers (ESEs) using SVMs
Background: Exonic splicing enhancers (ESEs) activate nearby splice sites and promote the inclusion (vs. exclusion) of exons in which they reside, while being a binding site for S...
Britta Mersch, Alexander Gepperth, Sándor S...
IPM
2011
118views more  IPM 2011»
14 years 5 months ago
Detecting spam blogs from blog search results
Blogging has been an emerging media for people to express themselves. However, the presence of spam-blogs (also known as splogs) may reduce the value of blogs and blog search engi...
Linhong Zhu, Aixin Sun, Byron Choi
FORTE
2008
15 years 2 days ago
Detecting Communication Protocol Security Flaws by Formal Fuzz Testing and Machine Learning
Network-based fuzz testing has become an effective mechanism to ensure the security and reliability of communication protocol systems. However, fuzz testing is still conducted in a...
Guoqiang Shu, Yating Hsu, David Lee