2012/10/16 by Max Welling, Welling, Max, Andrew E. Gelfand +3 · 2 citations
Computer Science · Mathematics · #Artificial Intelligence (cs.AI) #Bayesian Modeling and Causal Inference #Distributed Sensor Networks and Detection Algorithms #FOS: Computer and information sciences #Fuzzy Systems and Optimization
paper · pdf · doi:10.48550/arxiv.1210.4916
openalex publication_date 2012/10/16 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We introduce a new cluster-cumulant expansion (CCE) based on the fixed points of iterative belief propagation (IBP). This expansion is similar in spirit to the loop-series (LS) recently introduced in [1]. However, in contrast to the latter, the CCE enjoys the following important qualities: 1) it is defined for arbitrary state spaces 2) it is easily extended to fixed points of generalized belief propagation (GBP), 3) disconnected groups of variables will not contribute to the CCE and 4) the accuracy of the expansion empirically improves upon that of the LS. The CCE is based on the same Möbius transform as the Kikuchi approximation, but unlike GBP does not require storing the beliefs of the GBP-clusters nor does it suffer from convergence issues during belief updating.