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» Probabilistic models for discovering e-communities
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ICMLA
2007
13 years 10 months ago
Soft Failure Detection Using Factorial Hidden Markov Models
In modern business, educational, and other settings, it is common to provide a digital network that interconnects hardware devices for shared access by the users (e.g., in an of...
Guillaume Bouchard, Jean-Marc Andreoli
ICDM
2007
IEEE
132views Data Mining» more  ICDM 2007»
14 years 2 months ago
Learning What Makes a Society Tick
We present a machine learning methodology (models, algorithms, and experimental data) to discovering the agent dynamics that drive the evolution of the social groups in a communit...
Hung-Ching Chen, Mark K. Goldberg, Malik Magdon-Is...
CSB
2002
IEEE
109views Bioinformatics» more  CSB 2002»
14 years 1 months ago
Towards Automatic Clustering of Protein Sequences
Analyzing protein sequence data becomes increasingly important recently. Most previous work on this area has mainly focused on building classification models. In this paper, we i...
Jiong Yang, Wei Wang 0010
AAAI
2012
11 years 11 months ago
Identifying Bullies with a Computer Game
Current computer involvement in adolescent social networks (youth between the ages of 11 and 17) provides new opportunities to study group dynamics, interactions amongst peers, an...
Juan Fernando Mancilla-Caceres, Wen Pu, Eyal Amir,...
BMCBI
2007
105views more  BMCBI 2007»
13 years 8 months ago
Finding regulatory elements and regulatory motifs: a general probabilistic framework
Over the last two decades a large number of algorithms has been developed for regulatory motif finding. Here we show how many of these algorithms, especially those that model bind...
Erik van Nimwegen