Work

Multi-Way Block Models

Year: 2012

Type: article

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.Comparative simulation studies show that the four implementation algorithms achieve meaningful parameter estimates for the latent membership and block structure from correlation and network among the subjects.

Source: OhioLink ETD Center (Ohio Library and Information Network)

Author: Wang, Xiaopei

Institution: University of Cincinnati

Language: English

Topic: Bayesian Methods and Mixture Models

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funder: Strong

OpenAlex ID: W7021104027

FWCI:

Cites: 5

Cited by:

Related to: 10