研究者情報 | 神奈川大学

カナザワ　ユウイチロウ Kanazawa Yuichiro 金澤　雄一郎所属神奈川大学経済学部経済学科/現代ビジネス学科職種教授
言語種別	英語
発行・発表の年月	2024/06
形態種別	その他論文
標題	Parallelizing MCMC with Machine Learning Classifier and Its Criterion Based on Kullback-Leibler Divergence
執筆形態	共著
掲載誌名	arXiv>stat>arXiv:2406.11246
掲載区分	国外
担当区分	責任著者
概要	In the era of Big Data, analyzing high-dimensional and large datasets presents significant computational challenges. Although Bayesian statistics is well-suited for these complex data structures, the Markov Chain Monte Carlo (MCMC) method, which is essential for Bayesian estimation, suffers from computation cost because of its sequential nature. For faster and more effective computation, this paper introduces an algorithm to enhance a parallelizing MCMC method to handle this computation problem. We highlight the critical role of the overlapped area of posterior distributions calculated from partitioned data. We propose a method based on a machine learning classifier to identify and extract MCMC effectively draws from this area to approximate the actual posterior distribution.
DOI	https://doi.org/10.48550/arXiv.2406.11246