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Abstract : |
Abstract---A factor graph is a bipartite graph that expresses how a global function of several variables factors into a product of local functions. Factor graphs subsume many other graphical models, including Bayesian networks, Markov random fields, and Tanner graphs. We describe a general algorithm for computing "marginals " of the global function by distributed message-passing in the corresponding factor graph. A wide variety of algorithms developed in the artificial intelligence, statistics, signal processing, and digital communications communities can be derived as specific instances of this general algorithm, including Pearl's "belief propagation " and "belief revision " algorithms, the fast Fourier transform, the Viterbi algorithm, the forward/backward algorithm, and the iterative "turbo " decoding algorithm. 1, |
