学术报告
报告题目：Modeling high-dimensional time series
报 告 人：史晓平 博士
Thompson Rivers University
时 间：5月15日(星期二)上午10:00
地 点：统计研究院431教室
摘 要: Modeling high-dimensional time series is necessary in many fields such as neuroscience, signal processing, network evolution, text analysis, and image analysis. Such a time series may contain unknown multiple change-points. For example, the time of cell divisions can be accessed using an automatic embryo monitoring system by a time-lapse observation. When a cell divides at some time point, the distribution of pixel values in the corresponding frame will change, and hence the detection of cell divisions can be formulated as a multiple change-point problem. In this talk, a powerful graph-based change-point detection is introduced.
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统计研究院
2018年5月9日