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The Difficulties of Addressing Interdisciplinary Challenges at the Foundations of Data Science

2019/09/04 by Michael W. Mahoney, Mahoney, Michael W.
Business, Management and Accounting · Computer Science · Decision Sciences · Mathematics · #Big Data and Business Intelligence #Computers and Society (cs.CY) #FOS: Computer and information sciences #Scientific Computing and Data Management #Statistics Education and Methodologies #cs.CY

paper · pdf · doi:10.48550/arxiv.1909.03033

Appearing in SIAM News, SIGACT News, etc

arxiv created 2019/09/04 · openalex publication_date 2019/09/04 · arxiv updated 2019/09/09 · openalex created_date 2022/07/28 · openalex updated_date 2026/07/28

Abstract

The National Science Foundation's Transdisciplinary Research in Principles of Data Science (TRIPODS) program aims to integrate three areas central to the foundations of data by uniting the statistics, mathematics, and theoretical computer science research communities. The program aims to provide a model for funding cross-cutting research and facilitating interactions among the three disciplines. Challenges associated with orchestrating fruitful interactions are described.

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