Handbook of Big Data
暫譯: 大數據手冊

《大數據手冊》提供了對大規模數據集分析的最先進概述。該手冊匯集了統計學和計算機科學領域知名專家的貢獻，呈現了一系列精心策劃的技術，涵蓋了產業和學術界。因此，該文本使讀者對關鍵的統計和計算概念有了實用的理解，這些概念可以輕鬆應用於研究和實踐中。

本手冊在方法論、理論和應用方面提供了平衡的覆蓋，具體包括：

- 描述現代可擴展的方法來分析日益增長的大數據集
- 定義可用分析工具和技術的基本概念
- 詳細介紹計算統計和機器學習領域的社群間進展

《大數據手冊》還指出了需要進一步發展的領域，鼓勵大數據子專業（如基因組學、計算生物學和金融）研究人員之間加強溝通與合作。

Peter Bühlmann is a professor of statistics at ETH Zürich, Switzerland, fellow of the Institute of Mathematical Statistics, elected member of the International Statistical Institute, and co-author of the book titled Statistics for High-Dimensional Data: Methods, Theory and Applications. He was named a Thomson Reuters' 2014 Highly Cited Researcher in mathematics, served on various editorial boards and as editor of the Annals of Statistics, and delivered numerous presentations including a Medallion Lecture at the 2009 Joint Statistical Meetings, a read paper to the Royal Statistical Society in 2010, the 14th Bahadur Memorial Lectures at the University of Chicago, Illinois, USA, and other named lectures.

Petros Drineas is an associate professor in the Computer Science Department at Rensselaer Polytechnic Institute, Troy, New York, USA. He is the recipient of an Outstanding Early Research Award from Rensselaer Polytechnic Institute, an NSF CAREER award, and two fellowships from the European Molecular Biology Organization. He has served as a visiting professor at the US Sandia National Laboratories; visiting fellow at the Institute for Pure and Applied Mathematics, University of California, Los Angeles; long-term visitor at the Simons Institute for the Theory of Computing, University of California, Berkeley; program director in two divisions at the US National Science Foundation; and worked for industrial labs. He is a co-organizer of the series of workshops on Algorithms for Modern Massive Datasets and his research has been featured in numerous popular press articles.

Michael Kane is a member of the research faculty at Yale University, New Haven, Connecticut, USA. He is a winner of the American Statistical Association's Chambers Statistical Software Award for The Bigmemory Project, a set of software libraries that allow the R programming environment to accommodate large datasets for statistical analysis. He is a grantee on the Defense Advanced Research Projects Agency's XDATA project, part of the White House's Big Data Initiative, and on the Gates Foundation's Round 11 Grand Challenges Exploration. He has collaborated with companies including AT&T Labs Research, Paradigm4, Sybase, (a SAP company), and Oracle.

Mark van der Laan is the Jiann-Ping Hsu/Karl E. Peace professor of biostatistics and statistics at the University of California, Berkeley, USA. He is the inventor of targeted maximum likelihood estimation, a general semiparametric efficient estimation method that incorporates the state of the art in machine learning through the ensemble method super learning. He is the recipient of the 2005 COPPS Presidents' and Snedecor Awards, the 2005-van Dantzig Award, and the 2004 Spiegelman Award. He is also the founding editor of the International Journal of Biostatistics and the Journal of Causal Inference, and the co-author of more than 250 publications and various books.

彼得·比爾曼是瑞士蘇黎世聯邦理工學院的統計學教授，數學統計學會的會員，國際統計學會的當選成員，以及書籍《高維數據的統計：方法、理論與應用》的共同作者。他在2014年被評選為湯森路透的數學領域高被引研究者，曾擔任多個編輯委員會成員及《統計年鑑》的編輯，並在2009年聯合統計會議上發表了獎章講座，於2010年向英國皇家統計學會發表論文，並在美國伊利諾伊州芝加哥大學進行第14屆巴哈杜爾紀念講座及其他命名講座。

彼得羅斯·德里內斯是美國紐約州特洛伊的倫斯勒理工學院計算機科學系的副教授。他獲得了倫斯勒理工學院的傑出早期研究獎、國家科學基金會的CAREER獎，以及歐洲分子生物學組織的兩項獎學金。他曾擔任美國桑迪亞國家實驗室的訪問教授；加州大學洛杉磯分校純粹與應用數學研究所的訪問研究員；加州大學伯克利分校計算理論西蒙斯研究所的長期訪客；美國國家科學基金會兩個部門的計畫主任；並在工業實驗室工作。他是現代大規模數據集算法系列研討會的共同組織者，他的研究曾在多篇流行媒體文章中被報導。

邁克爾·凱恩是美國康涅狄格州紐哈芬的耶魯大學研究教職成員。他因《大記憶專案》獲得美國統計協會的查姆斯統計軟體獎，該專案是一組軟體庫，允許R編程環境處理大型數據集以進行統計分析。他是國防高級研究計畫局XDATA專案的資助者，該專案是白宮大數據倡議的一部分，並參與了比爾與梅琳達·蓋茨基金會的第11輪重大挑戰探索。他曾與包括AT&T實驗室研究、Paradigm4、Sybase（SAP公司）和Oracle等公司合作。

馬克·范德蘭是美國加州大學伯克利分校的賈安平·許/卡爾·E·皮斯生物統計學與統計學教授。他是目標最大似然估計的發明者，這是一種通用的半參數高效估計方法，通過集成方法超學習將最先進的機器學習技術納入其中。他是2005年COPPS總統獎和斯內德科獎、2005年范丹齊克獎以及2004年斯皮格曼獎的獲得者。他還是《國際生物統計學期刊》和《因果推斷期刊》的創始編輯，並共同撰寫了超過250篇出版物和各種書籍。