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» Sparse Subspace Clustering
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ICDE
2010
IEEE
222views Database» more  ICDE 2010»
15 years 11 days ago
Finding Clusters in subspaces of very large, multi-dimensional datasets
Abstract— We propose the Multi-resolution Correlation Cluster detection (MrCC), a novel, scalable method to detect correlation clusters able to analyze dimensional data in the ra...
Robson Leonardo Ferreira Cordeiro, Agma J. M. Trai...
ICML
2010
IEEE
15 years 2 months ago
Robust Subspace Segmentation by Low-Rank Representation
We propose low-rank representation (LRR) to segment data drawn from a union of multiple linear (or affine) subspaces. Given a set of data vectors, LRR seeks the lowestrank represe...
Guangcan Liu, Zhouchen Lin, Yong Yu
ICASSP
2010
IEEE
15 years 11 days ago
Independent subspace analysis with prior information for fMRI data
Independent component analysis (ICA) has been successfully applied for the analysis of functional magnetic resonance imaging (fMRI) data. However, independence might be too strong...
Sai Ma, Xi-Lin Li, Nicolle M. Correa, Tülay A...
DEXA
2009
Springer
151views Database» more  DEXA 2009»
15 years 8 months ago
Detecting Projected Outliers in High-Dimensional Data Streams
Abstract. In this paper, we study the problem of projected outlier detection in high dimensional data streams and propose a new technique, called Stream Projected Ouliter deTector ...
Ji Zhang, Qigang Gao, Hai H. Wang, Qing Liu, Kai X...
141
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PAKDD
2010
ACM
134views Data Mining» more  PAKDD 2010»
15 years 3 months ago
A Robust Seedless Algorithm for Correlation Clustering
Abstract. Finding correlation clusters in the arbitrary subspaces of highdimensional data is an important and a challenging research problem. The current state-of-the-art correlati...
Mohammad S. Aziz, Chandan K. Reddy