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» Distance Metric Learning for Conditional Anomaly Detection
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ATAL
2011
Springer
12 years 5 months ago
Online anomaly detection in unmanned vehicles
Autonomy requires robustness. The use of unmanned (autonomous) vehicles is appealing for tasks which are dangerous or dull. However, increased reliance on autonomous robots increa...
Eliahu Khalastchi, Gal A. Kaminka, Meir Kalech, Ra...
TJS
2010
182views more  TJS 2010»
13 years 3 months ago
A novel unsupervised classification approach for network anomaly detection by k-Means clustering and ID3 decision tree learning
This paper presents a novel host-based combinatorial method based on k-Means clustering and ID3 decision tree learning algorithms for unsupervised classification of anomalous and ...
Yasser Yasami, Saadat Pour Mozaffari
ISSRE
2003
IEEE
13 years 10 months ago
Anomalies as Precursors of Field Failures
Reproducing and learning from failures in deployed software is costly and difficult. Those activities can be facilitated, however, if the circumstances leading to a failure are p...
Sebastian G. Elbaum, Satya Kanduri, Anneliese Amsc...
ICDM
2010
IEEE
168views Data Mining» more  ICDM 2010»
13 years 3 months ago
Anomaly Detection Using an Ensemble of Feature Models
We present a new approach to semi-supervised anomaly detection. Given a set of training examples believed to come from the same distribution or class, the task is to learn a model ...
Keith Noto, Carla E. Brodley, Donna K. Slonim
SDM
2007
SIAM
146views Data Mining» more  SDM 2007»
13 years 6 months ago
ROAM: Rule- and Motif-Based Anomaly Detection in Massive Moving Object Data Sets
With recent advances in sensory and mobile computing technology, enormous amounts of data about moving objects are being collected. One important application with such data is aut...
Xiaolei Li, Jiawei Han, Sangkyum Kim, Hector Gonza...