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ICML
2008
IEEE
14 years 10 months ago
Modeling interleaved hidden processes
Hidden Markov models assume that observations in time series data stem from some hidden process that can be compactly represented as a Markov chain. We generalize this model by as...
Niels Landwehr
BMCBI
2006
142views more  BMCBI 2006»
13 years 9 months ago
Improving the Performance of SVM-RFE to Select Genes in Microarray Data
Background: Recursive Feature Elimination is a common and well-studied method for reducing the number of attributes used for further analysis or development of prediction models. ...
Yuanyuan Ding, Dawn Wilkins
CORR
2010
Springer
146views Education» more  CORR 2010»
13 years 9 months ago
Active Learning for Hidden Attributes in Networks
In many networks, vertices have hidden attributes that are correlated with the network's topology. For instance, in social networks, people are more likely to be friends if t...
Xiaoran Yan, Yaojia Zhu, Jean-Baptiste Rouquier, C...
BMCBI
2010
118views more  BMCBI 2010»
13 years 9 months ago
From learning taxonomies to phylogenetic learning: Integration of 16S rRNA gene data into FAME-based bacterial classification
Background: Machine learning techniques have shown to improve bacterial species classification based on fatty acid methyl ester (FAME) data. Nonetheless, FAME analysis has a limit...
Bram Slabbinck, Willem Waegeman, Peter Dawyndt, Pa...
MM
2005
ACM
160views Multimedia» more  MM 2005»
14 years 2 months ago
Putting active learning into multimedia applications: dynamic definition and refinement of concept classifiers
The authors developed an extensible system for video exploitation that puts the user in control to better accommodate novel situations and source material. Visually dense displays...
Ming-yu Chen, Michael G. Christel, Alexander G. Ha...