ICASSP
2011
IEEE
12 years 8 months ago
2011
IEEE
In particle filtering, resampling is the only step that cannot be fully parallelized. Recently, we have proposed algorithms for distributed resampling implemented on architecture...
TNN
2008
13 years 4 months ago
2008
This paper addresses the problem of the optimal design of numerical experiments for the construction of nonlinear surrogate models. We describe a new method, called learner disagre...
IJUFKS
2007
13 years 4 months ago
2007
Abstract. Resampling methods are among the best approaches to determine the number of clusters in prototype-based clustering. The core idea is that with the right choice for the nu...
CGF
2010
13 years 4 months ago
2010
Moving-Least-Squares (MLS) Surfaces undergoing large deformations need periodic regeneration of the point set (point-set resampling) so as to keep the point-set density quasi-unif...
BMCBI
2010
13 years 4 months ago
2010
Background: Many analyses of microarray association studies involve permutation, bootstrap resampling and crossvalidation, that are ideally formulated as embarrassingly parallel c...
VG
2003
13 years 5 months ago
2003
The transforming and rendering of discrete objects, such as traditional images (with or without depths) and volumes, can be considered as resampling problem – objects are recons...
DMIN
2007
13 years 6 months ago
2007
— One way to handle data mining problems where class prior probabilities and/or misclassification costs between classes are highly unequal is to resample the data until a new, d...
ECAI
2006
Springer
13 years 8 months ago
2006
Springer
Particle filtering (PF) for dynamic Bayesian networks (DBNs) with discrete-state spaces includes a resampling step which concentrates samples according to their relative weight in ...
FOCI
2007
IEEE
13 years 8 months ago
2007
IEEE
Abstract-- In this paper, we empirically analyze the convergence behavior of evolutionary algorithms (evolution strategies
AUSAI
2005
Springer
13 years 10 months ago
2005
Springer
Abstract. Principal Component Analysis (PCA) plus Linear Discriminant Analysis (LDA) (PCA+LDA) and LDA/QR are both two-stage methods that deal with the small sample size (SSS) prob...