Theoretical performance limits for message passing algorithms

消息传递算法的理论性能限制

• 批准号: 2104975
• 金额: --
• 依托单位: University of Cambridge
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2018
• 资助国家: 英国
• 起止时间: 2018 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2104975
• 关键词: Theoretical; performance; limits; message; passing

Message passing algorithms are low-complexity algorithms that achieve state-of-the-art empirical performance in a variety of applications such as error correction and lossy compression. However, they lack theoretical performance guarantees in many of these applications. This project will analyse the performance of message algorithms by developing rigorous density evolution equations. We will start with the problem of lossy compression, and then extend the techniques to other approximation and inference problems.The project directly relates to several EPSRC themes: Information and Communications Technologies (ICT), Engineering, Mathematical Sciences, and Healthcare Technologies, by making a strong contribution to the following research areas within these themes: Digital Signal Processing, Statistics and Applied Probability. It will help maintain UK academic excellence in data science by addressing an important set of research questions at the intersection of signal processing, information theory, and machine learning.

消息传递算法是低复杂度的算法，在纠错和有损压缩等各种应用中实现了最先进的经验性能。然而，它们在许多这样的应用中缺乏理论上的性能保证。该项目将通过开发严格的密度演化方程来分析消息算法的性能。我们将从有损压缩问题开始，然后将技术扩展到其他近似和推理问题。该项目直接涉及几个EPSRC主题：信息和通信技术(ICT)、工程、数学科学和医疗技术，在这些主题中的以下研究领域做出了强有力的贡献：数字信号处理、统计学和应用概率。它将通过解决信号处理、信息论和机器学习的交叉点上的一组重要研究问题，帮助保持英国在数据科学方面的学术卓越。