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118
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ICDM
2009
IEEE
132views Data Mining» more  ICDM 2009»
15 years 9 months ago
Bayesian Overlapping Subspace Clustering
Given a data matrix, the problem of finding dense/uniform sub-blocks in the matrix is becoming important in several applications. The problem is inherently combinatorial since th...
Qiang Fu, Arindam Banerjee
127
Voted
ICDM
2007
IEEE
159views Data Mining» more  ICDM 2007»
15 years 6 months ago
Spectral Regression: A Unified Approach for Sparse Subspace Learning
Recently the problem of dimensionality reduction (or, subspace learning) has received a lot of interests in many fields of information processing, including data mining, informati...
Deng Cai, Xiaofei He, Jiawei Han
ESANN
2008
15 years 4 months ago
A Method for Time Series Prediction using a Combination of Linear Models
This paper presents a new approach for time series prediction using local dynamic modeling. The proposed method is composed of three blocks: a Time Delay Line that transforms the o...
David Martínez-Rego, Oscar Fontenla-Romero,...
102
Voted
SDM
2004
SIAM
162views Data Mining» more  SDM 2004»
15 years 4 months ago
Subspace Clustering of High Dimensional Data
Clustering suffers from the curse of dimensionality, and similarity functions that use all input features with equal relevance may not be effective. We introduce an algorithm that...
Carlotta Domeniconi, Dimitris Papadopoulos, Dimitr...
142
Voted
ICIP
2010
IEEE
15 years 16 days ago
A new subspace learning method in Fourier domain for texture classification
This paper proposes a new texture classification approach. There are two main contributions in the proposed method. First, input texture images are transformed to the composite Fo...
Shu Liao, Albert C. S. Chung