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IJAR
2007
130views more  IJAR 2007»
15 years 6 months ago
Bayesian network learning algorithms using structural restrictions
The use of several types of structural restrictions within algorithms for learning Bayesian networks is considered. These restrictions may codify expert knowledge in a given domai...
Luis M. de Campos, Javier Gomez Castellano
JCM
2007
105views more  JCM 2007»
15 years 6 months ago
Generalization Capabilities Enhancement of a Learning System by Fuzzy Space Clustering
Abstract— We have used measurements taken on real network to enhance the performance of our radio network planning tool. A distribution learning technique is adopted to realize t...
Zakaria Nouir, Berna Sayraç, Benoît F...
JMLR
2002
138views more  JMLR 2002»
15 years 6 months ago
Learning Probabilistic Models of Link Structure
Most real-world data is heterogeneous and richly interconnected. Examples include the Web, hypertext, bibliometric data and social networks. In contrast, most statistical learning...
Lise Getoor, Nir Friedman, Daphne Koller, Benjamin...
PR
2010
156views more  PR 2010»
15 years 5 months ago
Semi-supervised clustering with metric learning: An adaptive kernel method
Most existing representative works in semi-supervised clustering do not sufficiently solve the violation problem of pairwise constraints. On the other hand, traditional kernel met...
Xuesong Yin, Songcan Chen, Enliang Hu, Daoqiang Zh...
CDC
2009
IEEE
138views Control Systems» more  CDC 2009»
15 years 4 months ago
Beyond local optimality: An improved approach to hybrid model learning
Abstract-- Local convergence is a limitation of many optimization approaches for multimodal functions. For hybrid model learning, this can mean a compromise in accuracy. We develop...
Stephanie Gil, Brian Williams