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ICASSP
2008
IEEE
14 years 2 months ago
A new Particle Filtering algorithm with structurally optimal importance function
Bayesian estimation in nonlinear stochastic dynamical systems has been addressed for a long time. Among other solutions, Particle Filtering (PF) algorithms propagate in time a Mon...
Boujemaa Ait-El-Fquih, François Desbouvries
AMT
2006
Springer
108views Multimedia» more  AMT 2006»
13 years 9 months ago
Efficient Frequent Itemsets Mining by Sampling
As the first stage for discovering association rules, frequent itemsets mining is an important challenging task for large databases. Sampling provides an efficient way to get appro...
Yanchang Zhao, Chengqi Zhang, Shichao Zhang
ICDM
2005
IEEE
138views Data Mining» more  ICDM 2005»
14 years 1 months ago
Labeling Unclustered Categorical Data into Clusters Based on the Important Attribute Values
Sampling has been recognized as an important technique to improve the efficiency of clustering. However, with sampling applied, those points which are not sampled will not have t...
Hung-Leng Chen, Kun-Ta Chuang, Ming-Syan Chen
ICML
2009
IEEE
14 years 8 months ago
Importance weighted active learning
We propose an importance weighting framework for actively labeling samples. This technique yields practical yet sound active learning algorithms for general loss functions. Experi...
Alina Beygelzimer, Sanjoy Dasgupta, John Langford
BC
2006
80views more  BC 2006»
13 years 7 months ago
Sparse Spatial Sampling for the Computation of Motion in Multiple Stages
The avian retino-tecto-rotundal pathway plays a central role in motion analysis and features complex connectivity. Yet, the relation between the pathway's structural arrangeme...
Alireza S. Mahani, Reza Khanbabaie, Harald Luksch,...