{"id":{"repo_id":"ohiolink","oai_identifier":"oai:etd.ohiolink.edu:ucin1342716695"},"canonical_url":"https://search.dev.ndltd.org/etd/ohiolink/oai:etd.ohiolink.edu:ucin1342716695","repository":{"repo_id":"ohiolink","name":"OhioLINK","base_url":"https://etd.ohiolink.edu/acprod/odb_etd/ws/oai/oai"},"display":{"title":"Multi-Way Block Models","abstract":"This dissertation investigates the Multi-Way Block Models proposed for mining inner structure of interaction between two sets of subjects. The Multi-Way Block Models generalize the Mixed Membership Stochastic Block Models (Airoldi et al., 2008) in multi-ways, as extensions in model settings allowing for different distributions of interactions between two groups of subjects. Moreover, the Multi-Way Block Models generalize model implementations to variational Bayesian, collapsed Gibbs sampling, collapsed variational Bayesian, and expectation propagation approaches. 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