报告题目 (Title)：An Introduction to Hyperparameter Optimization(超参数优化问题简介)
报告人 (Speaker)： 方慧 副教授（上海财经大学）
报告时间 (Time)：2021年12月14日(周二) 16:00 - 17:00
报告地点 (Place)：G507
邀请人(Inviter)：余长君
主办部门：理学院数学系
报告摘要：Machine learning (ML) has been widely exploited in both academia and industry. Building an effective machine learning model is a time-consuming process that involves obtaining an optimal model architecture with fine-tuned hyperparameters. Besides, recent interest in complex ML models with a relatively large volume of hyperparameters (e.g., autoML and deep learning methods) has resulted in an increasing volume of studies on hypeparameter optimization (HPO).
In this talk, I will first formally define the HPO problem, and give an overview of existing wok in this field of research. Secondly, three types of HPO methods, i.e., sampling-based, model-based and gradient-based, are elaborated. Finally, I will conclude the talk by summarizing challenging issues on the topic.
