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» Computing LTS Regression for Large Data Sets
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ICCV
2011
IEEE
12 years 7 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
14 years 2 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»
13 years 2 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»
13 years 7 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
14 years 1 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