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» Sampling Methods for Unsupervised Learning
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KDD
2002
ACM
138views Data Mining» more  KDD 2002»
16 years 5 months ago
Learning to match and cluster large high-dimensional data sets for data integration
Part of the process of data integration is determining which sets of identifiers refer to the same real-world entities. In integrating databases found on the Web or obtained by us...
William W. Cohen, Jacob Richman
ICARCV
2008
IEEE
184views Robotics» more  ICARCV 2008»
15 years 11 months ago
Learning informative point classes for the acquisition of object model maps
—This paper proposes a set of methods for building informative and robust feature point representations, used for accurately labeling points in a 3D point cloud, based on the typ...
Radu Bogdan Rusu, Zoltan Csaba Marton, Nico Blodow...
TNN
2008
82views more  TNN 2008»
15 years 4 months ago
Deterministic Learning for Maximum-Likelihood Estimation Through Neural Networks
In this paper, a general method for the numerical solution of maximum-likelihood estimation (MLE) problems is presented; it adopts the deterministic learning (DL) approach to find ...
Cristiano Cervellera, Danilo Macciò, Marco ...
ICPR
2008
IEEE
15 years 11 months ago
Pre-extracting method for SVM classification based on the non-parametric K-NN rule
With the increase of the training set’s size, the efficiency of support vector machine (SVM) classifier will be confined. To solve such a problem, a novel preextracting method f...
Deqiang Han, Chongzhao Han, Yi Yang, Yu Liu, Wenta...
JMLR
2006
107views more  JMLR 2006»
15 years 4 months ago
Consistency of Multiclass Empirical Risk Minimization Methods Based on Convex Loss
The consistency of classification algorithm plays a central role in statistical learning theory. A consistent algorithm guarantees us that taking more samples essentially suffices...
Di-Rong Chen, Tao Sun