Sciweavers

619 search results - page 71 / 124
» A Kernel Method for the Two-Sample Problem
Sort
View
JMLR
2010
161views more  JMLR 2010»
14 years 9 months ago
Training and Testing Low-degree Polynomial Data Mappings via Linear SVM
Kernel techniques have long been used in SVM to handle linearly inseparable problems by transforming data to a high dimensional space, but training and testing large data sets is ...
Yin-Wen Chang, Cho-Jui Hsieh, Kai-Wei Chang, Micha...
ICCV
2007
IEEE
15 years 8 months ago
Learning The Discriminative Power-Invariance Trade-Off
We investigate the problem of learning optimal descriptors for a given classification task. Many hand-crafted descriptors have been proposed in the literature for measuring visua...
Manik Varma, Debajyoti Ray
113
Voted
JCAM
2011
91views more  JCAM 2011»
14 years 5 months ago
Numerical solution of linear Volterra integral equations of the second kind with sharp gradients
Collocation methods are a well developed approach for the numerical solution of smooth and weakly-singular Volterra integral equations. In this paper we extend these methods, thro...
Samuel A. Isaacson, Robert M. Kirby
KDD
2008
ACM
104views Data Mining» more  KDD 2008»
16 years 2 months ago
Learning methods for lung tumor markerless gating in image-guided radiotherapy
In an idealized gated radiotherapy treatment, radiation is delivered only when the tumor is at the right position. For gated lung cancer radiotherapy, it is difficult to generate ...
Ying Cui, Jennifer G. Dy, Gregory C. Sharp, Brian ...
144
Voted
HPCN
1997
Springer
15 years 6 months ago
Parallel Solution of Irregular, Sparse Matrix Problems Using High Performance Fortran
For regular, sparse, linear systems, like those derived from regular grids, using High Performance Fortran (HPF) for iterative solvers is straightforward. However, for irregular ma...
Eric de Sturler, Damian Loher