CAREER: A New Look at the Fundamental Limits of Lossy Network Compression

职业生涯：重新审视有损网络压缩的基本极限有损压缩在我们的信息经济中扮演着关键的角色。到目前为止，我们作为一个社会产生的大多数信息都是图片、声音和视频，对于这类数据，有损压缩大大减少了传输和存储需求。该项目的目的是了解有损压缩的基本限制，特别是在主导当今通信基础设施的网络环境中。以前关于这个问题的工作并没有导致对有损网络压缩的基本理解，也没有对实际系统的设计产生重大影响。这项研究克服了以往工作的局限性，使用了两种新的方法。首先，过去高度笼统的模型被避开，而是倾向于规范的、具体的问题，这些问题同时更容易处理，也更与应用程序相关。基于PI的最新结果，该工作对高斯信源在二次失真约束下的有损网络压缩和离散信源在擦除失真约束下的有损网络压缩的基本极限有了全面和结论性的理解。其次，这些基本限制是在更现实的场景中研究的，在这些场景中，源、网络和允许的失真都以不可预测的方式变化。为了帮助学生学习如何创建既易于处理又适用于真实系统的概率和信息理论模型，研究生和本科生的现有课程正在进行改造，以更多地强调建模。该项目还包括重要的外联活动，包括向妇女和代表性不足的少数族裔工程本科生和农村高中生提供关于压缩的互动教程。

CAREER: A New Look at the Fundamental Limits of Lossy Network CompressionLossy compression plays a key role in our information economy. By far, most of the information that wegenerate as a society represents pictures, sounds, and videos, and for this kind of data, lossy compression yields a tremendous reduction in transmission and storage requirements. The aim of this project is to understand the fundamental limits of lossy compression,especially in the context of networks, which dominate today's communication infrastructure. Previous work on this problem has not led to a fundamental understanding of lossy network compression nor has it had a significant impact on the design of practical systems. This research overcomes the limitations of prior work using two novel approaches. First, the highly general models of the past are eschewed in favor of canonical, concrete problems that are simultaneously more tractable and more relevant to applications. Building on recent results of the PI, the work develops a comprehensive and conclusive understanding of the fundamental limits of lossy network compression for Gaussian sources under quadratic distortion constraints and discrete sources under erasure distortion constraints. Second, these fundamental limits are studied under more realistic scenarios in which the source, the network, and the allowable distortion all change in unpredictable ways. To help students learn how to create probabilistic and information-theoretic models that are tractable yet also applicable to real systems, existing courses at both the graduate and undergraduate level are being remade to include greater emphasis on modeling. The project also includes significant outreach, involving an interactive tutorial on compression delivered to women and underrepresented-minority engineering undergraduates and rural high-school students.