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» Local Adaptive Subspace Regression
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ICDM
2002
IEEE
158views Data Mining» more  ICDM 2002»
15 years 3 months ago
Adaptive dimension reduction for clustering high dimensional data
It is well-known that for high dimensional data clustering, standard algorithms such as EM and the K-means are often trapped in local minimum. Many initialization methods were pro...
Chris H. Q. Ding, Xiaofeng He, Hongyuan Zha, Horst...
ICASSP
2008
IEEE
15 years 4 months ago
Video denoising using higher order optimal space-time adaptation
The optimal spatial adaptation (OSA) method [1] proposed by Boulanger and Kervrann has proven to be quite effective for spatially adaptive image denoising. This method, in additio...
Hae Jong Seo, Peyman Milanfar
TSP
2010
14 years 5 months ago
Distributed sparse linear regression
The Lasso is a popular technique for joint estimation and continuous variable selection, especially well-suited for sparse and possibly under-determined linear regression problems....
Gonzalo Mateos, Juan Andrés Bazerque, Georg...
PVLDB
2008
107views more  PVLDB 2008»
14 years 8 months ago
Constrained locally weighted clustering
Data clustering is a difficult problem due to the complex and heterogeneous natures of multidimensional data. To improve clustering accuracy, we propose a scheme to capture the lo...
Hao Cheng, Kien A. Hua, Khanh Vu
NECO
1998
168views more  NECO 1998»
14 years 10 months ago
Constructive Incremental Learning from Only Local Information
We introduce a constructive, incremental learning system for regression problems that models data by means of spatially localized linear models. In contrast to other approaches, t...
Stefan Schaal, Christopher G. Atkeson