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KI
2007
Springer
13 years 9 months ago
Improving the Detection of Unknown Computer Worms Activity Using Active Learning
Detecting unknown worms is a challenging task. Extant solutions, such as anti-virus tools, rely mainly on prior explicit knowledge of specific worm signatures. As a result, after t...
Robert Moskovitch, Nir Nissim, Dima Stopel, Clint ...
TMI
2010
172views more  TMI 2010»
13 years 7 months 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...
PAMI
2011
13 years 4 months ago
Learning Linear Discriminant Projections for Dimensionality Reduction of Image Descriptors
This paper proposes a general method for improving image descriptors using discriminant projections. Two methods based on Linear Discriminant Analysis have been recently introduce...
Hongping Cai, Krystian Mikolajczyk, Jiri Matas
ICML
2008
IEEE
14 years 10 months ago
Sample-based learning and search with permanent and transient memories
We present a reinforcement learning architecture, Dyna-2, that encompasses both samplebased learning and sample-based search, and that generalises across states during both learni...
David Silver, Martin Müller 0003, Richard S. ...
ML
2010
ACM
155views Machine Learning» more  ML 2010»
13 years 7 months ago
On the infeasibility of modeling polymorphic shellcode - Re-thinking the role of learning in intrusion detection systems
Current trends demonstrate an increasing use of polymorphism by attackers to disguise their exploits. The ability for malicious code to be easily, and automatically, transformed in...
Yingbo Song, Michael E. Locasto, Angelos Stavrou, ...