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ASP
2003
Springer
13 years 9 months ago
Outlier Detection Using Default Logic
Default logic is used to describe regular behavior and normal properties. We suggest to exploit the framework of default logic for detecting outliers - individuals who behave in a...
Fabrizio Angiulli, Rachel Ben-Eliyahu-Zohary, Luig...
KDD
2005
ACM
205views Data Mining» more  KDD 2005»
13 years 10 months ago
Feature bagging for outlier detection
Outlier detection has recently become an important problem in many industrial and financial applications. In this paper, a novel feature bagging approach for detecting outliers in...
Aleksandar Lazarevic, Vipin Kumar
ICDM
2006
IEEE
226views Data Mining» more  ICDM 2006»
13 years 10 months ago
Converting Output Scores from Outlier Detection Algorithms into Probability Estimates
Current outlier detection schemes typically output a numeric score representing the degree to which a given observation is an outlier. We argue that converting the scores into wel...
Jing Gao, Pang-Ning Tan
MLDM
2007
Springer
13 years 10 months ago
Outlier Detection with Kernel Density Functions
Abstract. Outlier detection has recently become an important problem in many industrial and financial applications. In this paper, a novel unsupervised algorithm for outlier detec...
Longin Jan Latecki, Aleksandar Lazarevic, Dragolju...
MICCAI
2007
Springer
13 years 10 months ago
Shape-Based Myocardial Contractility Analysis Using Multivariate Outlier Detection
Abstract. This paper presents a new approach to regional myocardial contractility analysis based on inter-landmark motion (ILM) vectors and multivariate outlier detection. The prop...
Karim Lekadir, Niall Keenan, Dudley Pennell, Guang...
HPCC
2007
Springer
13 years 10 months ago
Continuous Adaptive Outlier Detection on Distributed Data Streams
In many applications, stream data are too voluminous to be collected in a central fashion and often transmitted on a distributed network. In this paper, we focus on the outlier det...
Liang Su, Weihong Han, Shuqiang Yang, Peng Zou, Ya...
ICDM
2008
IEEE
176views Data Mining» more  ICDM 2008»
13 years 10 months ago
Inlier-Based Outlier Detection via Direct Density Ratio Estimation
We propose a new statistical approach to the problem of inlier-based outlier detection, i.e., finding outliers in the test set based on the training set consisting only of inlier...
Shohei Hido, Yuta Tsuboi, Hisashi Kashima, Masashi...
MDM
2009
Springer
126views Communications» more  MDM 2009»
13 years 11 months ago
Outlier Detection in Ad Hoc Networks Using Dempster-Shafer Theory
Mobile Ad-hoc NETworks (MANETs) are known to be vulnerable to a variety of attacks due to lack of central authority or fixed network infrastructure. Many security schemes have bee...
Wenjia Li, Anupam Joshi
ACCV
2009
Springer
13 years 11 months ago
A Dynamic Programming Approach to Maximizing Tracks for Structure from Motion
We present a novel algorithm for improving the accuracy of structure from motion on video sequences. Its goal is to efficiently recover scene structure and camera pose by using dyn...
Jonathan Mooser, Suya You, Ulrich Neumann, Raphael...
MOBIHOC
2007
ACM
14 years 4 months ago
Outlier detection in sensor networks
Outlier detection has many important applications in sensor networks, e.g., abnormal event detection, animal behavior change, etc. It is a difficult problem since global informati...
Bo Sheng, Qun Li, Weizhen Mao, Wen Jin