U.S.-France Cooperative Research (INRIA): Symbolic Data Analysis Project

0093738 Billard美国三年奖-法国应用数学的合作研究涉及格鲁吉亚大学的Lynne Billard和多菲内巴黎大学的Edwin Diday以及法国罗克库尔的信息学和应用数学研究所（INRIA）。 研究人员将专注于开发分析符号数据的方法。该方法涉及科学计算结合数值和统计分析概念。该项目的双重目标是开发符号数据分析方法，将其扩展到更一般和复杂的数据，并审查需要进一步研究的领域的现有方法。 还将研究这些方法的数学基础和鲁棒性。 符号数据对于汇总大型数据集以使其易于管理进行分析非常有用。 目前存在很少的方法来分析符号数据，并将需要作为大型科学数据集的需求增加和符号数据变得更加普遍。该奖项代表了美国国家科学基金会和法国国家信息学和应用数学研究所（INRIA）的联合提案。 NSF将支付美国研究员和研究生的旅费和生活费。 INRIA将支持法国研究人员访问美国。该项目利用了法国研究人员的计算专业知识。他发展了符号数据的基本概念。 美国在统计和统计分析方面的专门知识对此起到了补充作用。

0093738BillardThis three-year award for U.S.-France cooperative research in applied mathematics involves Lynne Billard at the University of Georgia and Edwin Diday of the University of Paris, Dauphine, and the Institute for Research in Informatics and Applied Mathematics (INRIA) at Rocquencourt, France. The investigators will focus on developing methodologies for analyzing symbolic data. The approach involves scientific computing in conjunction with numerical and statistical analysis concepts. This project addresses the twin goals of developing methodologies for symbolic data analysis, extending it to more general and complex data, and the reviewing of current methods for areas that need further research. Mathematical foundation and robustness of these methods will also be studied. Symbolic data are useful for summarizing large data sets to render them manageable for analysis. Few methods currently exist to analyze symbolic data and will be needed as the demand for large scientific data sets increases and symbolic data become more prevalent. This award represents the US side of a joint proposal to the NSF and the French National Institute for Research in Informatics and Applied Mathematics (INRIA). NSF will cover travel funds and living expenses for the US investigator and graduate student. INRIA will support the visits of French researchers to the United States. The project takes advantage of the French investigator's computational expertise. He has developed the basic concepts involved in symbolic data. This is complemented by US expertise in statistics and statistical analysis.