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124
Voted
IDEAL
2004
Springer
15 years 7 months ago
2004
Springer
We study a stock trading method based on dynamic bayesian networks to model the dynamics of the trend of stock prices. We design a three level hierarchical hidden Markov model (HHM...
132
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SUM
2009
Springer
15 years 9 months ago
2009
Springer
Bayesian networks are probabilistic graphical models widely employed in AI for the implementation of knowledge-based systems. Standard inference algorithms can update the beliefs a...
119
Voted
SDM
2009
SIAM
15 years 11 months ago
2009
SIAM
Although a large body of work are devoted to finding communities in static social networks, only a few studies examined the dynamics of communities in evolving social networks. I...
116
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CVPR
2000
IEEE
16 years 4 months ago
2000
IEEE
The human figure exhibits complex and rich dynamic behavior that is both nonlinear and time-varying. However, most work on tracking and analysis of figure motion has employed eith...
123
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NIPS
2007
15 years 3 months ago
2007
Dynamic Bayesian networks are structured representations of stochastic processes. Despite their structure, exact inference in DBNs is generally intractable. One approach to approx...