Symposium

Mathematical Challenges for Machine Learning and Artificial Intelligence

November 11, 2021

2:00 PM - 4:00 PM (EST)

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Developments in the mathematical and statistical sciences are critical to the latest advances in machine learning and artificial intelligence. Join the National Academies for a virtual symposium on Thursday, November 11 from 2-4pm ET to discuss new innovations and future opportunities for mathematical research.

During the symposium, speakers will discuss how statistical theory helps build in protections for black box machine learning models, new approaches for making sense of high-dimensional and heterogenous data, novel methods for understanding causality, and future research opportunities in deep learning.

SYMPOSIUM SPEAKERS:

Sanjeev Arora, Princeton University
Emmanuel Candes, Stanford University
Pragya Sur, Harvard University
Caroline Uhler, Massachusetts Institute of Technology
Rebecca Willett, University of Chicago

This symposium is organized by the National Academies' Board on Mathematical Sciences and Analytics. Learn more about our work and sign up for our mailing list on our website.

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