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» Incremental Mixture Learning for Clustering Discrete Data
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ENGL
2007
89views more  ENGL 2007»
13 years 8 months ago
Similarity-based Heterogeneous Neural Networks
This research introduces a general class of functions serving as generalized neuron models to be used in artificial neural networks. They are cast in the common framework of comp...
Lluís A. Belanche Muñoz, Julio Jose ...
KDD
2010
ACM
277views Data Mining» more  KDD 2010»
14 years 9 days ago
Growing a tree in the forest: constructing folksonomies by integrating structured metadata
Many social Web sites allow users to annotate the content with descriptive metadata, such as tags, and more recently to organize content hierarchically. These types of structured ...
Anon Plangprasopchok, Kristina Lerman, Lise Getoor
SIGIR
2003
ACM
14 years 1 months ago
Collaborative filtering via gaussian probabilistic latent semantic analysis
Collaborative filtering aims at learning predictive models of user preferences, interests or behavior from community data, i.e. a database of available user preferences. In this ...
Thomas Hofmann
BIBM
2008
IEEE
142views Bioinformatics» more  BIBM 2008»
14 years 3 months ago
Using Global Sequence Similarity to Enhance Biological Sequence Labeling
Identifying functionally important sites from biological sequences, formulated as a biological sequence labeling problem, has broad applications ranging from rational drug design ...
Cornelia Caragea, Jivko Sinapov, Drena Dobbs, Vasa...
ECML
2001
Springer
14 years 1 months ago
Learning of Variability for Invariant Statistical Pattern Recognition
In many applications, modelling techniques are necessary which take into account the inherent variability of given data. In this paper, we present an approach to model class speci...
Daniel Keysers, Wolfgang Macherey, Jörg Dahme...