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ICASSP
2011
IEEE
9 years 2 months ago
Efficient distributed resampling for particle filters
In particle filtering, resampling is the only step that cannot be fully parallelized. Recently, we have proposed algorithms for distributed resampling implemented on architecture...
Balakumar Balasingam, Miodrag Bolic, Petar M. Djur...
TNN
2008
93views more  TNN 2008»
9 years 10 months ago
Towards the Optimal Design of Numerical Experiments
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...
S. Gazut, J.-M. Martinez, Gérard Dreyfus, Y...
IJUFKS
2007
108views more  IJUFKS 2007»
9 years 10 months ago
Resampling for Fuzzy Clustering
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...
Christian Borgelt
CGF
2010
147views more  CGF 2010»
9 years 10 months ago
Resampling Strategies for Deforming MLS Surfaces
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...
Joao Paulo Gois, Gustavo C. Buscaglia
BMCBI
2010
116views more  BMCBI 2010»
9 years 10 months ago
permGPU: Using graphics processing units in RNA microarray association studies
Background: Many analyses of microarray association studies involve permutation, bootstrap resampling and crossvalidation, that are ideally formulated as embarrassingly parallel c...
Ivo D. Shterev, Sin-Ho Jung, Stephen L. George, Ko...
VG
2003
10 years 12 hour ago
Hybrid Forward Resampling and Volume Rendering
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...
Xiaoru Yuan, Minh X. Nguyen, Hui Xu, Baoquan Chen
DMIN
2007
226views Data Mining» more  DMIN 2007»
10 years 3 days ago
Generative Oversampling for Mining Imbalanced Datasets
— 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...
Alexander Liu, Joydeep Ghosh, Cheryl Martin
ECAI
2006
Springer
10 years 2 months ago
Smoothed Particle Filtering for Dynamic Bayesian Networks
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 ...
Theodore Charitos
FOCI
2007
IEEE
10 years 2 months ago
Evolutionary Algorithms in the Presence of Noise: To Sample or Not to Sample
Abstract-- In this paper, we empirically analyze the convergence behavior of evolutionary algorithms (evolution strategies
Hans-Georg Beyer, Bernhard Sendhoff
AUSAI
2005
Springer
10 years 4 months ago
Resampling LDA/QR and PCA+LDA for Face Recognition
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...
Jun Liu, Songcan Chen
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