论文标题
大数据的贝叶斯统计方法的调查
A Survey of Bayesian Statistical Approaches for Big Data
论文作者
论文摘要
现代时代的特征是信息或大数据的时代。这激发了有关从这些数据中提取信息和见解的新方法的大量文献。一个自然的问题是，这些方法与大数据出现之前可用的方法有何不同。我们对已发表的研究进行了评论，该研究介绍了专门针对大数据的贝叶斯统计方法，并讨论了这些方法的报告和感知的好处。最后，我们解决了一个问题，即仅关注改进计算算法和基础架构是否足以面对大数据的挑战。
The modern era is characterised as an era of information or Big Data. This has motivated a huge literature on new methods for extracting information and insights from these data. A natural question is how these approaches differ from those that were available prior to the advent of Big Data. We present a review of published studies that present Bayesian statistical approaches specifically for Big Data and discuss the reported and perceived benefits of these approaches. We conclude by addressing the question of whether focusing only on improving computational algorithms and infrastructure will be enough to face the challenges of Big Data.
