Myles Hollander Distinguished Lectureship
This 2022 lectureship will take place on Wednesday, November 9th at 11:00 a.m.
FSU Announces Dr. Trevor Hastie as the 2022 Myles Hollander Distinguished Lecturer
The Department of Statistics at Florida State University is pleased to announce that Trevor Hastie, John A. Overdeck Professor of Mathematical Sciences, Professor of Statistics and Professor of Biomedical Data Science in the School of Humanities and Sciences at Stanford University, is the 2022 Myles Hollander Distinguished Lecturer. Hastie will present Cross-validation in Model Selection and Assessment.
For more information and to register for the event, please see the 2022 FSU Hollander Distinguished Lectureship.
About Dr. Trevor Hastie
Hastie received his bachelor's degree from Rhodes University, South Africa in 1976, his master's degree from the University of Cape Town in 1979, and his Ph.D. from Stanford University in 1984. Hastie's research focuses on applied statistics, specifically in the fields of statistical modeling, bioinformatics and machine learning. Before becoming a Stanford professor in 1994, he worked at AT&T Bell Laboratories for almost a decade, where he contributed to the development of the statistical modeling environment popular in the R computing system. Hastie has published six books and over 200 articles, and he has co-edited a large software library on modeling tools for statistical computing. Recent awards include the Breiman Award from the American Statistical Association in 2020 and the University of Bologna Sigillum Magnum in 2019. Hastie is an elected member of the Royal Netherlands Academy of Arts and Science and the U.S. National Academy of Sciences. He is a fellow of the American Statistical Association, the Institute of Mathematical Statistics and the Royal Statistical Society.
Lecture Abstract
Cross-validation is ubiquitous in data science, and is used for both model selection and assessment. Yet in some regards it is poorly understood. In this talk we discuss three aspects of CV:
• What CV estimates?
• Confidence intervals for prediction error using nested CV.
• Out-of-bag error for random-forests and standard error estimates.
The research discussed is joint work with Stephen Bates, a post-doctoral researcher at University of California, Berkeley; Samyak Rajanala, a doctoral student at Stanford University; and Rob Tibshirani, a statistics professor at Stanford.
This lecture is dedicated to the late Leo Breiman, a distinguished statistician at the University of California, Berkeley, and Colin Mallows, a renowned statistician who worked at Bell Labs and AT&T Labs for forty years.
More Information
Please see The 2022 Hollander Distinguished Lectureship web page for more information.
All attendees must register for the lecture, whether attending in-person or by Zoom!
The Myles Hollander Distinguished Lectureship is sponsored by:
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Elizabeth Slate
Professor
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