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COMAD
2008
13 years 9 months ago
Disk-Based Sampling for Outlier Detection in High Dimensional Data
We propose an efficient sampling based outlier detection method for large high-dimensional data. Our method consists of two phases. In the first phase, we combine a "sampling...
Timothy de Vries, Sanjay Chawla, Pei Sun, Gia Vinh...
CVPR
2008
IEEE
14 years 1 months ago
Subspace segmentation with outliers: A grassmannian approach to the maximum consensus subspace
Segmenting arbitrary unions of linear subspaces is an important tool for computer vision tasks such as motion and image segmentation, SfM or object recognition. We segment subspac...
Nuno Pinho da Silva, João Paulo Costeira
DAGSTUHL
2007
13 years 9 months ago
Subspace outlier mining in large multimedia databases
Abstract. Increasingly large multimedia databases in life sciences, ecommerce, or monitoring applications cannot be browsed manually, but require automatic knowledge discovery in d...
Ira Assent, Ralph Krieger, Emmanuel Müller, T...
JMLR
2010
153views more  JMLR 2010»
13 years 2 months ago
Feature Extraction for Outlier Detection in High-Dimensional Spaces
This work addresses the problem of feature extraction for boosting the performance of outlier detectors in high-dimensional spaces. Recent years have observed the prominence of mu...
Nguyen Hoang Vu, Vivekanand Gopalkrishnan
KDD
2005
ACM
205views Data Mining» more  KDD 2005»
14 years 28 days 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