报告题目：An introduction to Machine Learning and its Mathematical Framework for Error Analysis

报告时间：2024-05-13  14:30-15:30

报 告 人：冯寒 副教授 (香港城市大学）

报告地点：武汉大学理学院东北楼四楼报告厅

Abstract：The field of machine learning has revolutionized the way we approach complex problems and make intelligent decisions. In this talk, I am going to firstly give an introduction to machine learning with a journey through the key concepts, techniques, and methodologies that shape the field. Starting with a brief overview, we will explore the core integrentsof machine learning, highlighting its transformative applications across various domains. Subsequently I will focus on the mathematical frameworks that govern error analysis, including bias-variance tradeoffs, overfitting and underfitting, and model complexity. The mathematical analysis will enable us to understand and quantify the performance of machine learning algorithms. This includes a look at empirical risk minimization, generalization ability, and the role of hypothesis spaces.