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GECCO
2005
Springer
158views Optimization» more  GECCO 2005»
16 years 8 days ago
Applying both positive and negative selection to supervised learning for anomaly detection
This paper presents a novel approach of applying both positive selection and negative selection to supervised learning for anomaly detection. It first learns the patterns of the n...
Xiaoshu Hang, Honghua Dai
ECCV
2010
Springer
15 years 11 months ago
Discriminative Tracking by Metric Learning
We present a discriminative model that casts appearance modeling and visual matching into a single objective for visual tracking. Most previous discriminative models for visual tra...
CONEXT
2007
ACM
15 years 8 months ago
Detecting worm variants using machine learning
Network intrusion detection systems typically detect worms by examining packet or flow logs for known signatures. Not only does this approach mean worms cannot be detected until ...
Oliver Sharma, Mark Girolami, Joseph S. Sventek
AAAI
2010
15 years 8 months ago
Community-Guided Learning: Exploiting Mobile Sensor Users to Model Human Behavior
Modeling human behavior requires vast quantities of accurately labeled training data, but for ubiquitous people-aware applications such data is rarely attainable. Even researchers...
Daniel Peebles, Hong Lu, Nicholas D. Lane, Tanzeem...
CORR
2006
Springer
127views Education» more  CORR 2006»
15 years 6 months ago
Semi-Supervised Learning -- A Statistical Physics Approach
We present a novel approach to semisupervised learning which is based on statistical physics. Most of the former work in the field of semi-supervised learning classifies the point...
Gad Getz, Noam Shental, Eytan Domany