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PR
2007
139views more  PR 2007»
13 years 9 months ago
Learning the kernel matrix by maximizing a KFD-based class separability criterion
The advantage of a kernel method often depends critically on a proper choice of the kernel function. A promising approach is to learn the kernel from data automatically. In this p...
Dit-Yan Yeung, Hong Chang, Guang Dai
KDD
2006
ACM
170views Data Mining» more  KDD 2006»
14 years 10 months ago
Computer aided detection via asymmetric cascade of sparse hyperplane classifiers
This paper describes a novel classification method for computer aided detection (CAD) that identifies structures of interest from medical images. CAD problems are challenging larg...
Jinbo Bi, Senthil Periaswamy, Kazunori Okada, Tosh...
ICCV
2011
IEEE
12 years 10 months ago
Learning a Category Independent Object Detection Cascade
Cascades are a popular framework to speed up object detection systems. Here we focus on the first layers of a category independent object detection cascade in which we sample a l...
Esa Rahtu, Juho Kannala, Matthew Blaschko
SIAMSC
2011
219views more  SIAMSC 2011»
13 years 5 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...
SAS
2004
Springer
140views Formal Methods» more  SAS 2004»
14 years 3 months ago
Path-Sensitive Analysis for Linear Arithmetic and Uninterpreted Functions
We describe data structures and algorithms for performing a path-sensitive program analysis to discover equivalences of expressions involving linear arithmetic or uninterpreted fun...
Sumit Gulwani, George C. Necula