Sparse grid approximations and fitting using generalised combination techniques

使用广义组合技术的稀疏网格近似和拟合

• 批准号: DP0451503
• 负责人: Em/Prof Trygve Hegland
• 金额: $ 11.91万
• 依托单位: The Australian National University
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2004
• 资助国家: 澳大利亚
• 起止时间: 2004-01-01 至 2007-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP0451503
• 关键词: Sparse; grid; approximations; fitting; using

Sparse grid techniques provide an effective tool to deal with the computational curse of dimensionality which is a constant challenge in modelling complex data. The proposed research is aimed at the development and analysis of algorithms for data fitting with sparse grids using variants of the combination technique. The outcome of the research is a theory which will provide insights in the applicability, limitations and the convergence properties of the proposed algorithms. The outcomes will be widely applicable in modelling of large scale and complex data as is encountered in areas of bioinformatics, physics and experimental studies of complex systems.

稀疏的网格技术提供了处理的有效工具 维度的计算诅咒，这是一个持续的挑战 建模复杂数据。拟议的研究针对 开发和分析数据拟合数据的算法稀疏 使用组合技术的变体网格。结果 研究是一种理论，它将提供有关适用性的见解， 所提出的局限性和收敛性 算法。结果将广泛用于建模 大规模和复杂数据如在 复杂系统的生物信息学，物理和实验研究。