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» Outlier detection by active learning
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JSW
2007
138views more  JSW 2007»
13 years 8 months ago
Learning Problem and BCJR Decoding Algorithm in Anomaly-based Intrusion Detection Systems
— The anomaly-based intrusion detection systems examine current system activity do find deviations from normal system activity. The present paper proposes a method for normal act...
Veselina G. Jecheva, Evgeniya P. Nikolova
ICML
2006
IEEE
14 years 9 months ago
Active sampling for detecting irrelevant features
The general approach for automatically driving data collection using information from previously acquired data is called active learning. Traditional active learning addresses the...
Sriharsha Veeramachaneni, Emanuele Olivetti, Paolo...
ICASSP
2009
IEEE
14 years 3 months ago
Active learning for semi-supervised multi-task learning
We present an algorithm for active learning (adaptive selection of training data) within the context of semi-supervised multi-task classifier design. The semi-supervised multi-ta...
Hui Li, Xuejun Liao, Lawrence Carin
ICASSP
2011
IEEE
13 years 4 days ago
Fall detection in a smart room by using a fuzzy one class support vector machine and imperfect training data
In this paper, we propose an efficient and robust fall detection system by using a fuzzy one class support vector machine based on video information. Two cameras are used to capt...
Miao Yu, Syed Mohsen Naqvi, Adel Rhuma, Jonathon A...
SSDBM
2008
IEEE
114views Database» more  SSDBM 2008»
14 years 2 months ago
A General Framework for Increasing the Robustness of PCA-Based Correlation Clustering Algorithms
Abstract. Most correlation clustering algorithms rely on principal component analysis (PCA) as a correlation analysis tool. The correlation of each cluster is learned by applying P...
Hans-Peter Kriegel, Peer Kröger, Erich Schube...