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CIA
2008
Springer
13 years 9 months ago
Trust-Based Classifier Combination for Network Anomaly Detection
Abstract. We present a method that improves the results of network intrusion detection by integration of several anomaly detection algorithms through trust and reputation models. O...
Martin Rehák, Michal Pechoucek, Martin Gril...
PR
2008
85views more  PR 2008»
13 years 7 months ago
Quadratic boosting
This paper presents a strategy to improve the AdaBoost algorithm with a quadratic combination of base classifiers. We observe that learning this combination is necessary to get be...
Thang V. Pham, Arnold W. M. Smeulders
IVC
2002
148views more  IVC 2002»
13 years 7 months ago
Detecting lameness using 'Re-sampling Condensation' and 'multi-stream cyclic hidden Markov models'
A system for the tracking and classification of livestock movements is presented. The combined `tracker-classifier' scheme is based on a variant of Isard and Blakes `Condensa...
Derek R. Magee, Roger D. Boyle
FOCS
1992
IEEE
13 years 11 months ago
On the Fault Tolerance of Some Popular Bounded-Degree Networks
In this paper, we analyze the fault tolerance of several bounded-degree networks that are commonly used for parallel computation. Among other things, we show that an N-node butterf...
Frank Thomson Leighton, Bruce M. Maggs, Ramesh K. ...
SEMCO
2007
IEEE
14 years 1 months ago
Large-Margin Discriminative Training of Hidden Markov Models for Speech Recognition
Discriminative training has been a leading factor for improving automatic speech recognition (ASR) performance over the last decade. The traditional discriminative training, howev...
Dong Yu, Li Deng