【数学与统计及交叉学科前沿论坛------高端学术讲座第121场】

报告题目：Advances of Structural Dimension Reduction and Decomposition in Bayesian Networks

报告人：孙毅教授 新疆大学

报告时间：2024年10月08日（周二）20:30-21:30

报告地点：腾讯会议ID：574-372-292

报告摘要：Bayesian networks serve as a pivotal instrument for modeling high-dimensional uncertain and complex data. With the exponential growth of such data, the challenge of statistical inference in large-scale Bayesian networks has remained a focal point of research. This report will delve into the structural dimensionality reduction and decomposition of Bayesian networks, presenting our recent findings in this domain. We look forward to receiving guidance and assistance from experts on our research content, outcomes, and directions. We sincerely anticipate collaborations and opportunities to learn from everyone, aiming for mutual progress.

报告人简介：孙毅，新疆大学数学与系统科学学院 教授、硕士生导师；中国现场统计研究会新疆分会常务理事，因果推断与多元统计分会理事。主要从事图论、组合论，图模型与机器学习领域的研究，在国际期刊The Ramanujan Journal、Theoretical Computer Science，International Journal of Approximate Reasoning, Discrete Applied Mathematics等杂志上发表论文30余篇。主持各类基金5项，其中国家自然科学基金2项，国家博士后基金1项，自治区基金2项。