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» Prediction of Indoor Movements Using Bayesian Networks
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KDD
2003
ACM
148views Data Mining» more  KDD 2003»
14 years 8 months ago
Mining concept-drifting data streams using ensemble classifiers
Recently, mining data streams with concept drifts for actionable insights has become an important and challenging task for a wide range of applications including credit card fraud...
Haixun Wang, Wei Fan, Philip S. Yu, Jiawei Han
MOBICOM
2000
ACM
14 years 12 hour ago
Caching strategies in on-demand routing protocols for wireless ad hoc networks
An on-demand routing protocol for wireless ad hoc networks is one that searches for and attempts to discover a route to some destination node only when a sending node originates a...
Yih-Chun Hu, David B. Johnson
BMCBI
2008
107views more  BMCBI 2008»
13 years 7 months ago
A machine learning approach to explore the spectra intensity pattern of peptides using tandem mass spectrometry data
Background: A better understanding of the mechanisms involved in gas-phase fragmentation of peptides is essential for the development of more reliable algorithms for high-throughp...
Cong Zhou, Lucas D. Bowler, Jianfeng Feng
ECSCW
2001
13 years 9 months ago
The effects of network delays on group work in real-time groupware
Network delays are a fact of life when using real-time groupware over a wide area network such as the Internet. This paper looks at how network delays affect closelycoupled group w...
Carl Gutwin
NECO
2002
104views more  NECO 2002»
13 years 7 months ago
An Unsupervised Ensemble Learning Method for Nonlinear Dynamic State-Space Models
A Bayesian ensemble learning method is introduced for unsupervised extraction of dynamic processes from noisy data. The data are assumed to be generated by an unknown nonlinear ma...
Harri Valpola, Juha Karhunen