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» Fast normal vector compression with bounded error
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SGP
2007
13 years 6 months ago
Fast normal vector compression with bounded error
We present two methods for lossy compression of normal vectors through quantization using "base" polyhedra. The first revisits subdivision-based quantization. The second...
Eric J. Griffith, Michal Koutek, Frits H. Post
JMLR
2008
104views more  JMLR 2008»
13 years 4 months ago
Nearly Uniform Validation Improves Compression-Based Error Bounds
This paper develops bounds on out-of-sample error rates for support vector machines (SVMs). The bounds are based on the numbers of support vectors in the SVMs rather than on VC di...
Eric Bax
CIARP
2004
Springer
13 years 8 months ago
New Bounds and Approximations for the Error of Linear Classifiers
In this paper, we derive lower and upper bounds for the probability of error for a linear classifier, where the random vectors representing the underlying classes obey the multivar...
Luís G. Rueda
ECCV
2006
Springer
14 years 6 months ago
Integrating Surface Normal Vectors Using Fast Marching Method
i Integration of surface normal vectors is a vital component in many shape reconstruction algorithms that require integrating surface normals to produce their final outputs, the de...
Jeffrey Ho, Jongwoo Lim, Ming-Hsuan Yang, David J....
CORR
2011
Springer
148views Education» more  CORR 2011»
12 years 11 months ago
How well can we estimate a sparse vector?
The estimation of a sparse vector in the linear model is a fundamental problem in signal processing, statistics, and compressive sensing. This paper establishes a lower bound on t...
Emmanuel J. Candès, Mark A. Davenport