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发表时间:2018-10-08 阅读次数:399次
报告题目: Making Sense of Noisy Data: Some Issues and Methods
报 告 人:Grace Y. Yi
报告人所在单位:Department of Statistics and Actuarial Science University of Waterloo
报告日期:2018-10-08 星期一
报告时间:16:00-17:00
报告地点:Room 106, Shanghai Center for Mathematical Sciences
  
报告摘要:

Thanks to the advancement of modern technology in acquiring data, massive data with diverse features and big volume are becoming more accessible than ever. The impact of big data is significant. While the abundant volume of data presents great opportunities for researchers to extract useful information for new knowledge gain and sensible decision making, big data present great challenges. A very important, sometimes overlooked challenge is the quality and provenance of the data. Big data are not automatically useful; big data are often raw and involve considerable noise. Typically, the challenges presented by noisy data with measurement error, missing observations and high dimensionality are particularly intriguing. Noisy data with these features arise ubiquitously from various fields including health sciences, epidemiological studies, environmental studies, survey research, economics, and so on. In this talk, I will discuss the issues induced from noisy data and some methods of handling such data.

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本年度学院报告总序号:217

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