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» Computing LTS Regression for Large Data Sets
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ICCV
2011
IEEE
13 years 11 months ago
Regression from Local Features for Viewpoint and Pose Estimation
In this paper we propose a framework for learning a regression function form a set of local features in an image. The regression is learned from an embedded representation that re...
Marwan Torki, Ahmed Elgammal
ISVC
2009
Springer
15 years 6 months ago
Parallel 3D Image Segmentation of Large Data Sets on a GPU Cluster
In this paper, we propose an inherent parallel scheme for 3D image segmentation of large volume data on a GPU cluster. This method originates from an extended Lattice Boltzmann Mod...
Aaron Hagan, Ye Zhao
TNN
2010
176views Management» more  TNN 2010»
14 years 6 months ago
Sparse approximation through boosting for learning large scale kernel machines
Abstract--Recently, sparse approximation has become a preferred method for learning large scale kernel machines. This technique attempts to represent the solution with only a subse...
Ping Sun, Xin Yao
CSDA
2007
152views more  CSDA 2007»
14 years 11 months ago
Robust variable selection using least angle regression and elemental set sampling
In this paper we address the problem of selecting variables or features in a regression model in the presence of both additive (vertical) and leverage outliers. Since variable sel...
Lauren McCann, Roy E. Welsch
CIKM
2007
Springer
15 years 6 months ago
Regularized locality preserving indexing via spectral regression
We consider the problem of document indexing and representation. Recently, Locality Preserving Indexing (LPI) was proposed for learning a compact document subspace. Different from...
Deng Cai, Xiaofei He, Wei Vivian Zhang, Jiawei Han