Dimensionality reduction: methodology and applications

降维：方法和应用

• 批准号: 327487-2009
• 负责人: GhodsiBoushehri, Ali
• 金额: $ 1.38万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2010
• 资助国家: 加拿大
• 起止时间: 2010-01-01 至 2011-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=457953
• 关键词: Dimensionality; reduction; methodology; applications

This research focuses on simple representations of complex data sets. Three specific problems of interest are data mining, finding a sequence of actions to achieve a particular outcome (planning), and maintaining a representation of one's location (localization). This work is applicable to numerous areas in which meaningful information must be extracted from extremely large and multivariate sequential data sets. In these domains, action taken at a data point (e.g. taking a treatment by a patient) has immediate effect on consequent observations. The goal is to find a representation in which the actions correspond to simple mathematical transformations such as translation and rotation.

本研究侧重于复杂数据集的简单表示。我们感兴趣的三个具体问题是数据挖掘、找到实现特定结果的一系列行动（规划）和维护一个人的位置表示（本地化）。这项工作适用于许多领域，在这些领域中，有意义的信息必须从非常大的和多变量序列数据集中提取出来。在这些领域，在数据点采取的行动（例如，患者采取的治疗）对随后的观察结果具有直接影响。目标是找到一种表示，其中动作对应于简单的数学转换，如平移和旋转。