Efficient Algorithms with Practical Applications

高效算法与实际应用

• 批准号: 9531028
• 负责人: Ming-Yang Kao
• 金额: $ 10万
• 依托单位: Duke University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1997
• 资助国家: 美国
• 起止时间: 1997-07-15 至 2000-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9531028&HistoricalAwards=false
• 关键词: Efficient; Algorithms; Practical; Applications

The goal of the proposed project is to design efficient algorithms applicable to security and computational issues that are core concerns of statistical agencies and database vendors. Results obtained from the project will be implemented to test theoretical models as well as to advance technology transfers. Building on the PI's completed work on statistical data security, a number of specific research directions are pursued to further determine the computational complexity of detecting and protecting sensitive information in highly useful types of statistical data bases. These directions involve techniques from a variety of algorithms areas including combinatorial optimization, dynamic algorithms, graph algorithms, linear algebraic algorithms, and online competitive analysis. It is expected that algorithmic insights and techniques obtained from this project will be useful in various application areas in addition to statistical data security, such as relational databases and secret sharing schemes.

拟议项目的目标是设计适用于安全和计算问题的有效算法，这些问题是统计机构和数据库供应商的核心关切。 从该项目中获得的结果将用于测试理论模型以及推进技术转让。 在PI完成的统计数据安全工作的基础上，进行了一些具体的研究方向，以进一步确定在非常有用的统计数据库类型中检测和保护敏感信息的计算复杂性。 这些方向涉及各种算法领域的技术，包括组合优化，动态算法，图形算法，线性代数算法和在线竞争分析。 预计从该项目中获得的算法见解和技术将在各种应用领域中有用，除了统计数据安全，如关系数据库和秘密共享计划。