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KDD
2006
ACM
180views Data Mining» more  KDD 2006»
15 years 10 months ago
Learning the unified kernel machines for classification
Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...
Steven C. H. Hoi, Michael R. Lyu, Edward Y. Chang
AIRS
2006
Springer
15 years 1 months ago
Learning to Separate Text Content and Style for Classification
Many text documents naturally have two kinds of labels. For example, we may label web pages from universities according to their categories, such as "student" or "fa...
Dell Zhang, Wee Sun Lee
NN
2002
Springer
125views Neural Networks» more  NN 2002»
14 years 9 months ago
Generalized relevance learning vector quantization
We propose a new scheme for enlarging generalized learning vector quantization (GLVQ) with weighting factors for the input dimensions. The factors allow an appropriate scaling of ...
Barbara Hammer, Thomas Villmann
ICML
1998
IEEE
15 years 10 months ago
Bayesian Network Classification with Continuous Attributes: Getting the Best of Both Discretization and Parametric Fitting
In a recent paper, Friedman, Geiger, and Goldszmidt [8] introduced a classifier based on Bayesian networks, called Tree Augmented Naive Bayes (TAN), that outperforms naive Bayes a...
Moisés Goldszmidt, Nir Friedman, Thomas J. ...
HUC
2010
Springer
14 years 8 months ago
Routine as resource for the design of learning systems
Even though the coordination of kids’ activities is largely successful, the modern dual income family still regularly experiences breakdowns in their practices. Families often r...
Scott Davidoff