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94
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IJAR
2008
119views more  IJAR 2008»
15 years 22 days ago
Adapting Bayes network structures to non-stationary domains
When an incremental structural learning method gradually modifies a Bayesian network (BN) structure to fit observations, as they are read from a database, we call the process stru...
Søren Holbech Nielsen, Thomas D. Nielsen
92
Voted
ICASSP
2011
IEEE
14 years 4 months ago
Time-evolving modeling of social networks
A statistical framework for modeling and prediction of binary matrices is presented. The method is applied to social network analysis, specifically the database of US Supreme Cou...
Eric Wang, Jorge Silva, Rebecca Willett, Lawrence ...
106
Voted
IDA
2010
Springer
15 years 2 months ago
Data Mining for Modeling Chiller Systems in Data Centers
We present a data mining approach to model the cooling infrastructure in data centers, particularly the chiller ensemble. These infrastructures are poorly understood due to the lac...
Debprakash Patnaik, Manish Marwah, Ratnesh K. Shar...
122
Voted
IEEECIT
2010
IEEE
14 years 11 months ago
A Learning Spectrum Hole Prediction Model for Cognitive Radio Systems
—In this paper, we present a new spectrum-hole prediction model for cognitive radio (CR) systems based on the IEEE 802.11 wireless local areas networks. We have also analyzed the...
Zhigang Wen, Chunxiao Fan, Xiaoying Zhang, Yuexin ...
ACL
2007
15 years 2 months ago
Much ado about nothing: A social network model of Russian paradigmatic gaps
A number of Russian verbs lack 1sg nonpast forms. These paradigmatic gaps are puzzling because they seemingly contradict the highly productive nature of inflectional systems. We m...
Robert Daland, Andrea D. Sims, Janet Pierrehumbert