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KI
2007
Springer
13 years 8 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 ...
PERCOM
2005
ACM
14 years 2 months ago
Applying Active Space Principles to Active Classrooms
Recent developments in pervasive computing have enabled new features for collaboration and instrumentation in educational technology systems. An infrastructure for the integration...
Chad Peiper, David Warden, Ellick Chan, Roy H. Cam...
WWW
2006
ACM
14 years 9 months ago
Large-scale text categorization by batch mode active learning
Large-scale text categorization is an important research topic for Web data mining. One of the challenges in large-scale text categorization is how to reduce the amount of human e...
Steven C. H. Hoi, Rong Jin, Michael R. Lyu
ICML
1997
IEEE
14 years 8 days ago
Efficient Feature Selection in Conceptual Clustering
Feature selection has proven to be a valuable technique in supervised learning for improving predictive accuracy while reducing the number of attributes considered in a task. We i...
Mark Devaney, Ashwin Ram
IROS
2008
IEEE
141views Robotics» more  IROS 2008»
14 years 3 months ago
Active sensing based dynamical object feature extraction
— This paper presents a method to autonomously extract object features that describe their dynamics from active sensing experiences. The model is composed of a dynamics learning ...
Shun Nishide, Tetsuya Ogata, Ryunosuke Yokoya, Jun...