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» Detecting worm variants using machine learning
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ICML
2007
IEEE
16 years 4 months ago
Learning distance function by coding similarity
We consider the problem of learning a similarity function from a set of positive equivalence constraints, i.e. 'similar' point pairs. We define the similarity in informa...
Aharon Bar-Hillel, Daphna Weinshall
120
Voted
ALT
2006
Springer
16 years 10 days ago
Iterative Learning from Positive Data and Negative Counterexamples
A model for learning in the limit is defined where a (so-called iterative) learner gets all positive examples from the target language, tests every new conjecture with a teacher ...
Sanjay Jain, Efim B. Kinber
BMVC
2010
15 years 1 months ago
Generalized RBF feature maps for Efficient Detection
Kernel methods yield state-of-the-art performance in certain applications such as image classification and object detection. However, large scale problems require machine learning...
Sreekanth Vempati, Andrea Vedaldi, Andrew Zisserma...
146
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ICDM
2010
IEEE
168views Data Mining» more  ICDM 2010»
15 years 1 months ago
Anomaly Detection Using an Ensemble of Feature Models
We present a new approach to semi-supervised anomaly detection. Given a set of training examples believed to come from the same distribution or class, the task is to learn a model ...
Keith Noto, Carla E. Brodley, Donna K. Slonim
SP
2006
IEEE
148views Security Privacy» more  SP 2006»
15 years 9 months ago
SubVirt: Implementing malware with virtual machines
Attackers and defenders of computer systems both strive to gain complete control over the system. To maximize their control, both attackers and defenders have migrated to low-leve...
Samuel T. King, Peter M. Chen, Yi-Min Wang, Chad V...