报告时间：8月18日15:00-17：00报告地点：滴水湖国际软件学院502报告名称一：Non-convex optimization approach to maximum hands-off control （Prof. Masaaki Nagahara, Hiroshima University, Japan ）报告摘要:This talk presents a novel computational method for sparse control, also known as maximum hands-off control, using non-convex penalty f
报告名称：Learning to Generate the Moving World: Video Generative Models and Their Applications报告时间：8月13日15:00报告地点：数学馆201腾讯会议：151-993-578报告摘要:Generative AI is rapidly evolving beyond static images and text, entering the dynamic and complex domain of video generation. From producing realistic video conten
报告名称：From Probabilistic Testing to Certifiable AI: Large Language Models and Neuro-Symbolic Reasoning for Verifiable Autonomous Systems报告时间：8月9日14:00报告地点：理科大楼B211腾讯会议：298 825 900（密码：101812）报告摘要:Learning-enabled Cyber-Physical Systems (LE-CPS), such as autonomous vehicles and drones, pose significant
报告名称：Software Reliability Growth Model Averaging: Theory and Empirical Validation报告时间：7月29日15:00报告地点：滴水湖国际软件学院502报告摘要:Accurate prediction of the cumulative number of software faults as well as quantitative software reliability has been still a challenging issue in software reliability for a long
报告名称：Frontiers in Intelligent Software Data Analytics: An Initial Exploration报告时间：7月29日15:00报告地点：滴水湖国际软件学院502室报告摘要:Intelligent Software Data Analytics has long been a focal research topic in software engineering. With the emergence of new AI technologies such as deep learning and large language mo
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