Modern Data Modeling: Cross-Fertilization of the Two Cultures

Jianqing Fan, Cong Ma, Kaizheng Wang, Ziwei Zhu
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引用次数: 3

Abstract

Abstract:The past two decades have witnessed deep cross-fertilization between the two cultures—statistics (data/generative modeling) and machine learning (algorithmic modeling), which is in stark contrast to the scene pictured in Breiman's inspiring work. In light of this major confluence, we find it helpful to single out a few salient examples showcasing the impacts of one to the other, and the research progress out of them. We point out in the end that the current big data era especially requires joint efforts from both cultures in order to address some common challenges including decentralized data analysis, privacy, fairness, etc.
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现代数据建模:两种文化的交叉受精
摘要:在过去的二十年里,统计学(数据/生成建模)和机器学习(算法建模)这两种文化之间发生了深刻的交叉融合,这与布莱曼鼓舞人心的作品中的场景形成了鲜明对比。鉴于这一主要汇合点,我们发现挑出几个突出的例子来展示一个对另一个的影响以及其中的研究进展是很有帮助的。我们最后指出,当前的大数据时代尤其需要两种文化的共同努力,以应对一些共同的挑战,包括去中心化的数据分析、隐私、公平等。
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