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Belief Propagation (BP), a distributed, message-passing algorithm, has been widely used in different disciplines including information theory, artificial intelligence, statistics and optimization problems in graphical models such as Bayesian networks and Markov random fields. Despite BP algorithm has a great success in many application fields and many progress about BP algorithm has been made, the...
Traffic classification is currently a significant challenge for network monitoring and management. Feature selection is an effective method to realize dimension reduction and decrease redundant information. To realize accurate traffic classification at lower price of evaluations, a hybrid feature subset selection method is proposed on the base of sliding block, the size of which is flexible according...
A novel kind of recurrent neural network (called varying-parameter convergent-differential neural-network, VP-CDNN) is proposed in this paper for online solving linear time-varying equations. Different from traditional gradient-base neural network (called GNN) with scalar-valued error functions, such new VP-CDNN is designed based on matrix-valued or vector-valued error functions and their coefficients...
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