Browsing by Author "GUHANIYOGI, RAJARSHI"

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    Strategies for Distributed Bayesian Inference with Independent and Spatio-temporally Correlated Data
    (2024-05-06) GUHANIYOGI, RAJARSHI
    Due to recent advancements in technology, the utilization of massive datasets, whether independent or correlated, has become prevalent across various fields such as forestry, ocean science, neuroimaging, and public health. Traditional Bayesian statistical approaches for analyzing such datasets operate on the assumption that all data from different units are stored and processed centrally. This centralized data processing paradigm necessitates significant computing and storage resources at the central server, while also raising valid privacy concerns for individual units contributing data. To address these challenges, a comprehensive Bayesian analysis framework has been devised, allowing for approximate Bayesian inference in a decentralized manner, with model computation distributed across multiple machines. This article presents a review of pertinent methods in distributed Bayesian inference developed in recent years, catering to both independent and spatio-temporally correlated data.