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ICTAI
2008
IEEE
16 years 14 days ago
Using Imputation Techniques to Help Learn Accurate Classifiers
It is difficult to learn good classifiers when training data is missing attribute values. Conventional techniques for dealing with such omissions, such as mean imputation, general...
Xiaoyuan Su, Taghi M. Khoshgoftaar, Russell Greine...
ICPR
2010
IEEE
15 years 8 months ago
A Semi-Supervised Gaussian Mixture Model for Image Segmentation
In this paper, the results of a semi-supervised approach based on the Expectation-Maximisation algorithm for model-based clustering are presented. We show in this work that, if th...
Adolfo Martínez-Usó, F. Pla, Jose Martínez Soto...
ESANN
2003
15 years 7 months ago
Modeling of growing networks with directional attachment and communities
In this paper, we propose a new network growth model and its learning algorithm to more precisely model such a real-world growing network as the Web. Unlike the conventional model...
Masahiro Kimura, Kazumi Saito, Naonori Ueda
ICDE
2003
IEEE
143views Database» more  ICDE 2003»
16 years 7 months ago
Index-Based Approximate XML Joins
XML data integration tools are facing a variety of challenges for their efficient and effective operation. Among these is the requirement to handle a variety of inconsistencies or...
Sudipto Guha, Nick Koudas, Divesh Srivastava, Ting...
163
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ICML
2008
IEEE
16 years 6 months ago
Fully distributed EM for very large datasets
In EM and related algorithms, E-step computations distribute easily, because data items are independent given parameters. For very large data sets, however, even storing all of th...
Jason Wolfe, Aria Haghighi, Dan Klein