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Title: Quantifying criticality based on the observed data, and application to AI (基于观测数据来量化临界状态的理论、及人工智能的应用) Speaker: Luonan Chen （陈洛南）, Key Laboratory of Systems Biology, Chinese Academy of Sciences Chair： 蒋田仔 研究员，中国科学院自动化研究所 Time： 2018年11月7日，下午2:30-3:30 Venue：自动化大厦13层第二会议室 |
Abstract:
Identifying early-warning signals of a critical transition for a complex system is difficult, especially when the target system is constantly perturbed by noise, which makes the traditional methods fail due to the strong fluctuations of the observed data. In this work, we show that the critical transition is not traditional state-transition but probability distribution-transition when the noise is not sufficiently small, which, however, is a ubiquitous case in real systems. We present a model-free computational method to detect the warning signals before such transitions. The key idea behind is a strategy: “making big noise smaller” by a distribution-embedding scheme, which transforms the data from the observed state-variables with big noise to their distribution-variables with small noise, and thus makes the traditional criteria effective because of the significantly reduced fluctuations. Specifically, increasing the dimension of the observed data by moment expansion that changes the system from state-dynamics to probability distribution-dynamics, we derive new data in a higher dimensional space but with much smaller noise. Then, we develop a criterion based on the dynamic network marker (DNM) to signal the impending critical transition using the transformed higher dimensional data. We also demonstrate the effectiveness of our method in biological, ecological and financial systems.
Biography:
陈洛南，1984年获华中科技大学电气工程学士学位；1988年获日本东北大学系统科学硕士学位；1991年获日本东北大学系统科学博士学位。1997年起任日本大阪产业大学副教授；2000年起任美国加州大学洛杉矶分校(UCLA)访问教授；2002年起任日本大阪产业大学教授；2009年4月起任日本东京大学教授(兼)；2009年10月至今任中科院系统生物学重点实验室执行主任，研究员。现任中国运筹学会《计算系统生物学分会》理事长，IEEE-SMC《系统生物学委员会》主席，中日韩国际系统生物学会组织（Trisys）的轮值主席，中国细胞生物学会《功能基因组学与系统生物学分会》副会长，中国药理学会《网络药理学专业委员会》副主任委员，上海市临床生物信息学研究所副所长，国家基金委重大研究计划专家组专家，国家重点研发计划首席科学家。主要从事计算系统生物学和大数据分析的研究工作。近年来，在计算系统生物学和非线性动力学等研究领域发表了300余篇SCI期刊论文及10余部编著书籍 (h-index: 57)。