腾讯会议 ：230-265-259

主讲人姓名 ：赵鹏，南京大学人工智能学院副研究员

主讲人简介 ： 赵鹏博士，南京大学人工智能学院副研究员。2021年于南京大学获博士学位。研究方向为机器学习，主要包括开放环境机器学习、稳健在线学习的理论与方法。研究成果发表在JMLR、COLT、ICML、NeurIPS等国际顶级学术期刊和会议。曾担任多个学术期刊和会议的审稿人或（高级）程序委员会成员，AAAI 2019组织委员会成员（流程主席）。

报告题目 ：Non-stationary Online Learning: An Online Ensemble Framework

报告摘要 ：Online learning is an important learning paradigm for dealing with sequential prediction and decision-making problems. The non-stationarity issue is a central challenge for modern online learning, given that many real-world data streams are collected in open environments and the distributions are naturally changing over time. In this talk, we will introduce our recent efforts on this topic. We introduce dynamic regret as the performance measure to guide the algorithm design, and then propose the online ensemble framework to optimize the measure. The framework can yield fruitful algorithmic and theoretical results for many important online learning problems and attain best-known or optimal guarantees.