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» On Kernel Methods for Relational Learning
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128
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ICTAI
2005
IEEE
15 years 9 months ago
Latent Process Model for Manifold Learning
In this paper, we propose a novel stochastic framework for unsupervised manifold learning. The latent variables are introduced, and the latent processes are assumed to characteriz...
Gang Wang, Weifeng Su, Xiangye Xiao, Frederick H. ...
DAGM
2007
Springer
15 years 7 months ago
Efficient Learning of Neural Networks with Evolutionary Algorithms
Abstract. In this article we present EANT2, a method that creates neural networks (NNs) by evolutionary reinforcement learning. The structure of NNs is developed using mutation ope...
Nils T. Siebel, Jochen Krause, Gerald Sommer
138
Voted
BIBE
2009
IEEE
131views Bioinformatics» more  BIBE 2009»
15 years 7 months ago
Learning Scaling Coefficient in Possibilistic Latent Variable Algorithm from Complex Diagnosis Data
—The Possibilistic Latent Variable (PLV) clustering algorithm is a powerful tool for the analysis of complex datasets due to its robustness toward data distributions of different...
Zong-Xian Yin
114
Voted
EMNLP
2008
15 years 5 months ago
Learning Graph Walk Based Similarity Measures for Parsed Text
We consider a parsed text corpus as an instance of a labelled directed graph, where nodes represent words and weighted directed edges represent the syntactic relations between the...
Einat Minkov, William W. Cohen
154
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JMLR
2010
132views more  JMLR 2010»
14 years 10 months ago
Learning Gradients: Predictive Models that Infer Geometry and Statistical Dependence
The problems of dimension reduction and inference of statistical dependence are addressed by the modeling framework of learning gradients. The models we propose hold for Euclidean...
Qiang Wu, Justin Guinney, Mauro Maggioni, Sayan Mu...