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» Statistical Learning of Arbitrary Computable Classifiers
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ICCV
2001
IEEE
14 years 9 months ago
Learning Image Statistics for Bayesian Tracking
This paper describes a framework for learning probabilistic models of objects and scenes and for exploiting these models for tracking complex, deformable, or articulated objects i...
Hedvig Sidenbladh, Michael J. Black
KDD
2010
ACM
272views Data Mining» more  KDD 2010»
13 years 11 months ago
Beyond heuristics: learning to classify vulnerabilities and predict exploits
The security demands on modern system administration are enormous and getting worse. Chief among these demands, administrators must monitor the continual ongoing disclosure of sof...
Mehran Bozorgi, Lawrence K. Saul, Stefan Savage, G...
CVPR
2001
IEEE
14 years 9 months ago
Feature Reduction and Hierarchy of Classifiers for Fast Object Detection in Video Images
We present a two-step method to speed-up object detection systems in computer vision that use Support Vector Machines (SVMs) as classifiers. In a first step we perform feature red...
Bernd Heisele, Thomas Serre, Sayan Mukherjee, Toma...
PAM
2005
Springer
14 years 17 days ago
Self-Learning IP Traffic Classification Based on Statistical Flow Characteristics
A number of key areas in IP network engineering, management and surveillance greatly benefit from the ability to dynamically identify traffic flows according to the applications re...
Sebastian Zander, Thuy T. T. Nguyen, Grenville J. ...
FLAIRS
2008
13 years 9 months ago
One-Pass Learning Algorithm for Fast Recovery of Bayesian Network
An efficient framework is proposed for the fast recovery of Bayesian network classifier. A novel algorithm, called Iterative Parent-Child learningBayesian Network Classifier (IPC-...
Shunkai Fu, Michel Desmarais, Fan Li