Modern Data Modeling: Cross-Fertilization of the Two Cultures

Jianqing Fan, Cong Ma, Kaizheng Wang, Ziwei Zhu
{"title":"Modern Data Modeling: Cross-Fertilization of the Two Cultures","authors":"Jianqing Fan, Cong Ma, Kaizheng Wang, Ziwei Zhu","doi":"10.1353/obs.2021.0023","DOIUrl":null,"url":null,"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.","PeriodicalId":74335,"journal":{"name":"Observational studies","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Observational studies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1353/obs.2021.0023","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.
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。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
0.80
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信