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ICASSP
2009
IEEE
15 years 4 months ago
A Bayesian NETWORKS approach for dialog modeling: The fusion BN
Bayesian Networks, BNs, are suitable for mixed-initiative dialog modeling allowing a more flexible and natural spoken interaction. This solution can be applied to identify the in...
Fernando F. Fernández-Martínez, Javi...
WCET
2008
14 years 11 months ago
INFER: Interactive Timing Profiles based on Bayesian Networks
We propose an approach for timing analysis of software-based embedded computer systems that builds on the established probabilistic framework of Bayesian networks. We envision an ...
Michael Zolda
FLAIRS
2006
14 years 11 months ago
Decomposing Local Probability Distributions in Bayesian Networks for Improved Inference and Parameter Learning
A major difficulty in building Bayesian network models is the size of conditional probability tables, which grow exponentially in the number of parents. One way of dealing with th...
Adam Zagorecki, Mark Voortman, Marek J. Druzdzel
IEEECIT
2010
IEEE
14 years 8 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 ...
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RSFDGRC
2005
Springer
134views Data Mining» more  RSFDGRC 2005»
15 years 3 months ago
The Computational Complexity of Inference Using Rough Set Flow Graphs
Pawlak recently introduced rough set flow graphs (RSFGs) as a graphical framework for reasoning from data. Each rule is associated with three coefficients, which have been shown t...
Cory J. Butz, Wen Yan, Boting Yang