报告主题:

Multi-objective evolutionary neural architecture search: Communication efficiency, privacy preservation, and adversarial robustness

报告时间：

2023年7月20日15:00-16:00

报告地点：

beat365中文官方网站310会议室

报告摘要:

This talk presents multi-objective approaches to evolutionary neural architecture search in centralized and distributed environments. We introduce multi-objective evolutionary algorithms that aim to enhance computational efficiency and reduce communication cost in privacy-preserving federated neural architecture search. In addition, surrogate-assisted evolutionary search for neural network architectures that are robust to multiple adversarial attacks are presented.

主讲人：

Yaochu Jin is an Alexander von Humboldt Professor for Artificial Intelligence endowed by the German Federal Ministry of Education and Research, with the Faculty of Technology, Bielefeld University, Germany. He is also a Distinguished Chair, Professor in Computational Intelligence, Department of Computer Science, University of Surrey, Guildford, U.K. He was a “Finland Distinguished Professor” of University of Jyväskylä, Finland, “Changjiang Distinguished Visiting Professor”, Northeastern University, China, and “Distinguished Visiting Scholar”, University of Technology Sydney, Australia. His main research interests include multi-objective and data-driven evolutionary optimization, evolutionary multi-objective learning, trustworthy AI, and evolutionary developmental AI.

Prof Jin is presently the President-Elect of the IEEE Computational Intelligence Society and the Editor-in-Chief of Complex & Intelligent Systems. He was named by the Web of Science as “a Highly Cited Researcher” from 2019 to 2022 consecutively. He is a Member of Academia Europaea and Fellow of IEEE.

金耀初是德国联邦教育和研究部与德国比勒菲尔德大学技术学院共同授予的人工智能亚历山大·冯·洪堡教授。是英国吉尔福德萨里大学计算机科学系的杰出主席、计算智能教授。曾任芬兰于韦斯屈莱大学“芬兰特聘教授”、东北大学“长江特聘客座教授”、澳大利亚悉尼科技大学“特聘访问学者”。主要研究方向包括多目标和数据驱动的进化优化、进化多目标学习、可信人工智能和进化发展人工智能。

金教授目前是IEEE计算智能学会的当选主席，也是《复杂与智能系统》杂志的主编。他于2019年至2022年连续被Web of Science评为“高被引研究员”。他是欧洲科学院的成员和IEEE的研究员。