机器学习与数学优化高级研讨班

"Machine Learning and Mathematical Optimization" Tianyuan Mathematics advanced seminar will use the relationship between machine learning and mathematical optimization as the starting point, and based on the latest research advances in machine learning, it will mainly discuss the core mathematical optimization problems and the adopted ones that are closely related to machine learning some important optimization techniques are actively integrated into the mathematical background knowledge, mathematical models and important optimization algorithms involved in the field of machine learning research, focusing on new theories and methods generated by the combination of machine learning and mathematical optimization, and implementing personal offline research and learning a discussion format combining online discussions with discussion groups and meetings (short courses and academic cutting-edge lectures). This advanced seminar adheres to the interdisciplinary and cutting-edge nature of the discipline, and conforms to the development trend of applied mathematics. While adhering to the traditional research of mathematical optimization, it explores new areas of cross-research. The holding of this advanced seminar will provide young scholars engaged in mathematical optimization and related fields with opportunities to broaden their horizons and improve their level, promote the development and improvement of machine learning theory, and also promote the further development of mathematical optimization.

“机器学习与数学优化”天元数学高级研讨班以机器学习与数学优化的关系为切入点，以机器学习最新研究进展为基础，主要研讨机器学习所紧密相关的核心数学优化问题和所采用的一些重要优化技术手段，积极融入机器学习研究领域涉及的数学背景知识、数学模型及其重要优化算法，重点关注机器学习与数学优化的结合所产生的新理论和新方法，施行个人平时线下研究学习、研讨小组线上讨论与集中会议（短课程和学术前沿讲座等）研讨相结合的研讨形式。本次高级研讨班秉持学科交叉性和学科前沿性，顺应应用数学的发展趋势；在坚持数学优化传统研究的同时，探寻新的交叉研究领域。本次高级研讨班的举行将为从事数学优化及相关领域的年轻学者提供开拓视野和提高水平的机会，促进机器学习理论的发展与完善，推动数学优化的进一步发展。

“机器学习与数学优化”天元数学高级研讨班以机器学习与数学优化的关系为切入点，以机器学习最新研究进展及应用为基础，主要研讨机器学习所紧密相关的核心数学优化问题和所采用的一些重要优化技术手段，融入机器学习研究领域涉及的数学背景知识、数学模型及其重要优化算法，重点关注机器学习与数学优化的结合所产生的新理论和新方法。综合根据新冠疫情防控的实际需要，实行线上与线下相结合，集中报告研讨和分散讨论相结合。具体而言主要施行线上专家研究前沿学术报告、线下集中短课程和学员个人平时线下集中学习及研讨小组线上讨论、人工智能交叉学科线上论坛、优秀学员的学习研究进展线上汇报与知名专家线上点评等多种研讨形式。本次高级研讨班秉持学科交叉性和学科前沿性，顺应应用数学的发展趋势；在坚持数学优化传统研究的同时，探寻新的交叉研究领域。本次高级研讨班共吸引近1000人次参与到各类线上线下的研讨活动中，引起很大反响，得到广泛好评，为从事数学优化及相关领域的年轻学者提供开拓视野和提高水平的机会，促进机器学习理论的发展与完善，推动数学优化的进一步发展。