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JMLR
2002
106views more  JMLR 2002»
13 years 7 months ago
Some Greedy Learning Algorithms for Sparse Regression and Classification with Mercer Kernels
We present some greedy learning algorithms for building sparse nonlinear regression and classification models from observational data using Mercer kernels. Our objective is to dev...
Prasanth B. Nair, Arindam Choudhury 0002, Andy J. ...
SCALESPACE
2005
Springer
14 years 26 days ago
Sparse Finite Element Level-Sets for Anisotropic Boundary Detection in 3D Images
Level-Set methods have been successfully applied to 2D and 3D boundary detection problems. The geodesic active contour model has been particularly successful. Several algorithms fo...
Martin Weber, Andrew Blake, Roberto Cipolla
CORR
2011
Springer
209views Education» more  CORR 2011»
12 years 11 months ago
Analysis and Improvement of Low Rank Representation for Subspace segmentation
We analyze and improve low rank representation (LRR), the state-of-the-art algorithm for subspace segmentation of data. We prove that for the noiseless case, the optimization mode...
Siming Wei, Zhouchen Lin
AAAI
2012
11 years 9 months ago
Colorization by Matrix Completion
Given a monochrome image and some manually labeled pixels, the colorization problem is a computer-assisted process of adding color to the monochrome image. This paper proposes a n...
Shusen Wang, Zhihua Zhang
AAECC
2007
Springer
111views Algorithms» more  AAECC 2007»
13 years 7 months ago
When cache blocking of sparse matrix vector multiply works and why
Abstract. We present new performance models and a new, more compact data structure for cache blocking when applied to the sparse matrixvector multiply (SpM×V) operation, y ← y +...
Rajesh Nishtala, Richard W. Vuduc, James Demmel, K...