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Activity Number: 93
Type: Roundtables
Date/Time: Monday, August 1, 2016 : 7:00 AM to 8:15 AM
Sponsor: Section on Statistical Learning and Data Science
Abstract #319064
Title: What Can Statistics Learn from Machine Learning? And Vice Versa?
Author(s): Ryan Tibshirani and Edward Henry Kennedy*
Companies: Carnegie Mellon University
Keywords: Statistics ; Machine Learning ; Data Science
Abstract:

Compared to machine learning, statistics is an old and well-established field of research. Machine learning, being relatively young, has recently gained an enormous amount of attention in both academia and industry. Are these the same disciplines? Are they fundamentally different, and how? What can statistics learn from machine learning? And vice versa? Have we set ourselves up to compete with machine learning, or does the future hold a more collaborative and communal relationship? Come to this roundtable and we will discuss these issues. Suggested reading: "Statistical Modeling: The Two Cultures," by Leo Breiman, available at https://projecteuclid.org/euclid.ss/1009213726; "Rise of the Machines," by Larry Wasserman, available at www.stat.cmu.edu/~larry/Wasserman.pdf; and "50 Years of Data Science," by David Donoho, available at http://courses.csail.mit.edu/18.337/2015/docs/50YearsDataScience.pdf.


Authors who are presenting talks have a * after their name.

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