摘要翻译：
本书是一本致力于纪念耶胡达·瓦尔迪的论文集。耶胡达2005年1月13日意外去世时，他是罗格斯大学统计系主任。2005年10月21日至22日，约150位来自统计学、电信、生物医学工程、生物信息学、生物统计学和流行病学等不同领域的顶尖学者聚集在罗格斯大学，以纪念他。这次会议是关于“复杂数据集和反问题：层析成像，网络，以及更远”的，由编辑组织的。目前的收集包括在会议上提出的研究工作，以及耶胡达的同事的贡献。会议的主题是网络和涉及不完整数据和统计反问题的其他重要和新兴研究领域。我们周围的网络非常丰富：通信、计算机、交通、社会和能源只是其中的几个例子。随着信息时代网络数据的大量收集，这一领域引起了统计学和计算机工程研究人员以及电信运营商和政府机构的极大关注。然而，很少有统计工具用于分析网络数据，因为它们通常由复杂的图结构网络拓扑上的时变和相互依赖的通信协议所控制。这些和其他重要技术中的许多原型应用可以被视为具有复杂、海量、高维和可能有偏见/不完全数据的统计逆问题。这个统一的反问题的主题特别适合于一个专门纪念耶胡达的会议和卷。事实上，他对这些领域做出了有影响力的贡献，尤其是在医学断层扫描、有偏见的数据、统计反问题和网络断层扫描方面。
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英文标题：
《Complex Datasets and Inverse Problems. Tomography, Networks and Beyond》
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作者：
Regina Liu, William Strawderman, Cun-Hui Zhang
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最新提交年份：
2007
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分类信息：

一级分类：Mathematics        数学
二级分类：Statistics Theory        统计理论
分类描述：Applied, computational and theoretical statistics: e.g. statistical inference, regression, time series, multivariate analysis, data analysis, Markov chain Monte Carlo, design of experiments, case studies
应用统计、计算统计和理论统计：例如统计推断、回归、时间序列、多元分析、数据分析、马尔可夫链蒙特卡罗、实验设计、案例研究
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一级分类：Statistics        统计学
二级分类：Statistics Theory        统计理论
分类描述：stat.TH is an alias for math.ST. Asymptotics, Bayesian Inference, Decision Theory, Estimation, Foundations, Inference, Testing.
Stat.Th是Math.St的别名。渐近，贝叶斯推论，决策理论，估计，基础，推论，检验。
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英文摘要：
  This book is a collection of papers dedicated to the memory of Yehuda Vardi. Yehuda was the chair of the Department of Statistics of Rutgers University when he passed away unexpectedly on January 13, 2005. On October 21--22, 2005, some 150 leading scholars from many different fields, including statistics, telecommunications, biomedical engineering, bioinformatics, biostatistics and epidemiology, gathered at Rutgers in a conference in his honor. This conference was on ``Complex Datasets and Inverse Problems: Tomography, Networks, and Beyond,'' and was organized by the editors. The present collection includes research work presented at the conference, as well as contributions from Yehuda's colleagues. The theme of the conference was networks and other important and emerging areas of research involving incomplete data and statistical inverse problems. Networks are abundant around us: communication, computer, traffic, social and energy are just a few examples. As enormous amounts of network data are collected in this information age, the field has attracted a great amount of attention from researchers in statistics and computer engineering as well as telecommunication providers and various government agencies. However, few statistical tools have been developed for analyzing network data as they are typically governed by time-varying and mutually dependent communication protocols sitting on complicated graph-structured network topologies. Many prototypical applications in these and other important technologies can be viewed as statistical inverse problems with complex, massive, high-dimensional and possibly biased/incomplete data. This unifying theme of inverse problems is particularly appropriate for a conference and volume dedicated to the memory of Yehuda. Indeed he made influential contributions to these fields, especially in medical tomography, biased data, statistical inverse problems, and network tomography.
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PDF链接：
https://arxiv.org/pdf/708.113