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» Detecting worm variants using machine learning
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ALT
2009
Springer
15 years 11 months ago
Iterative Learning from Texts and Counterexamples Using Additional Information
Abstract. A variant of iterative learning in the limit (cf. [LZ96]) is studied when a learner gets negative examples refuting conjectures containing data in excess of the target la...
Sanjay Jain, Efim B. Kinber
BMCBI
2006
134views more  BMCBI 2006»
15 years 2 months ago
Application of machine learning in SNP discovery
Background: Single nucleotide polymorphisms (SNP) constitute more than 90% of the genetic variation, and hence can account for most trait differences among individuals in a given ...
Lakshmi K. Matukumalli, John J. Grefenstette, Davi...
TMI
2010
172views more  TMI 2010»
15 years 27 days ago
Comparison of AdaBoost and Support Vector Machines for Detecting Alzheimer's Disease Through Automated Hippocampal Segmentation
Abstract— We compared four automated methods for hippocampal segmentation using different machine learning algorithms (1) hierarchical AdaBoost, (2) Support Vector Machines (SVM)...
Jonathan H. Morra, Zhuowen Tu, Liana G. Apostolova...
ICSE
2004
IEEE-ACM
16 years 2 months ago
Finding Latent Code Errors via Machine Learning over Program Executions
This paper proposes a technique for identifying program properties that indicate errors. The technique generates machine learning models of program properties known to result from...
Yuriy Brun, Michael D. Ernst
168
Voted
ECBS
2007
IEEE
188views Hardware» more  ECBS 2007»
15 years 4 months ago
Behavior Analysis-Based Learning Framework for Host Level Intrusion Detection
Machine learning has great utility within the context of network intrusion detection systems. In this paper, a behavior analysis-based learning framework for host level network in...
Haiyan Qiao, Jianfeng Peng, Chuan Feng, Jerzy W. R...