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Keynote and Invited Speakers will deliver their lectures live through WebEx
https://purdue.webex.com/meet/aselvite
on the dates and times detailed below.
"Be approximately right rather than exactly wrong."
"Be approximately right rather than exactly wrong."
~ John W. Tukey, Statistician
~ John W. Tukey, Statistician
Morgane Austern
Morgane Austern
Title: To split or not to split that is the question: From cross validation to debiased machine learning.
Department of Statistics
Harvard Universisty
Mikhail Belkin
Mikhail Belkin
Title: From classical statistics to modern deep learning
Halicioğlu Data Science Institute
University of California, San Diego
Gitta Kutyniok
Gitta Kutyniok
Title: Reliable AI: Successes, Challenges, and Limitations
Mathematisches Institut
Ludwig-Maximilians-Universität München
Lester Mackey
Lester Mackey
Title: Doing Some Good with Machine Learning
Microsoft Research New England & Stanford University
Lester Mackey
Yang Liu
Yang Liu
Title: Early detection of fake news on social media
School of Sciences
Indiana University - Kokomo
Marie-Laure Charpignon
Marie-Laure Charpignon
Title: Causal inference in medical records: applications to drug repurposing for dementia
MIT Institute for Data, Systems, and Society
Massachusetts Institute of Technology
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