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PAMI
2008
139views more  PAMI 2008»
15 years 6 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 9 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 6 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
CGF
2008
165views more  CGF 2008»
15 years 6 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»
15 years 1 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...