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PAMI
2008
139views more  PAMI 2008»
15 years 3 months ago
A Fast Algorithm for Learning a Ranking Function from Large-Scale Data Sets
We consider the problem of learning a ranking function that maximizes a generalization of the Wilcoxon-Mann-Whitney statistic on the training data. Relying on an -accurate approxim...
Vikas C. Raykar, Ramani Duraiswami, Balaji Krishna...
PAMI
2012
13 years 5 months ago
BRIEF: Computing a Local Binary Descriptor Very Fast
Binary descriptors are becoming increasingly popular as a means to compare feature points very fast and while requiring comparatively small amounts of memory. The typical approach...
Michael Calonder, Vincent Lepetit, Mustafa Öz...
DCC
2004
IEEE
16 years 3 months ago
Fast Near-Lossless or Lossless Compression of Large 3D Neuro-Anatomical Images
3D neuro-anatomical images and other volumetric data sets are important in many scientific and biomedical fields. Since such sets may be extremely large, a scalable compression me...
Rongkai Zhao, Michael Gabriel, Geneva G. Belford
145
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CGF
2008
165views more  CGF 2008»
15 years 3 months ago
GPU-based Fast Ray Casting for a Large Number of Metaballs
Metaballs are implicit surfaces widely used to model curved objects, represented by the isosurface of a density field defined by a set of points. Recently, the results of particle...
Yoshihiro Kanamori, Zoltan Szego, Tomoyuki Nishita
SIAMSC
2011
219views more  SIAMSC 2011»
14 years 10 months ago
Fast Algorithms for Bayesian Uncertainty Quantification in Large-Scale Linear Inverse Problems Based on Low-Rank Partial Hessian
We consider the problem of estimating the uncertainty in large-scale linear statistical inverse problems with high-dimensional parameter spaces within the framework of Bayesian inf...
H. P. Flath, Lucas C. Wilcox, Volkan Akcelik, Judi...