Mathematical Challenges for Machine Learning and Artificial Intelligence
Event Information
About this event
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.
LOGIN INSTRUCTIONS
Watch the livestream and submit questions for our speakers on the event page at: https://www.nationalacademies.org/event/11-11-2021/mathematical-challenges-for-machine-learning-and-artificial-intelligence
The direct livestream link is: https://livestream.com/accounts/7036396/events/9899654
Submit questions for our speakers using sli.do at https://app.sli.do/event/0flfad7m
If you register on this page, you'll also receive an email with login instructions prior to the event.
Organizer NASEM Math and Statistics
Organizer of Mathematical Challenges for Machine Learning and Artificial Intelligence
The Board on Mathematical Sciences and Analytics (BMSA) of the National Academies of Sciences, Engineering, and Medicine leads activities in the mathematical sciences at the National Academies in topic areas including from applied mathematics, scientific computing, and risk analysis.
The Committee on Applied and Theoretical Statistics (CATS) of the National Academies of Sciences, Engineering, and medicine organizes studies and events focusing on the statistical sciences, big data and data science, statistical education, the use of statistics, and issues affecting the field. CATS occupies a pivotal position in the statistical community, providing expertise in methodology and policy formation.
