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Activity Number: 278 - Emerging Ideas in Predictive Inference
Type: Invited
Date/Time: Tuesday, July 30, 2019 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistical Learning and Data Science
Abstract #300624 Presentation
Title: Recent Advances in Conformal Prediction
Author(s): Larry Wasserman*
Companies: Carnegie Mellon University
Keywords: prediction; distribution-free; exchangeability
Abstract:

Conformal prediction is a method for distribution-free prediction that assumes only exchangeability. In this talk, I'll review the conformal prediction and how it can be applied to a variety of problems. I will also explain how some problems, such as clustering, can be re-cast as prediction problems. Then I will discuss the problem of detecting lack of exchangeability and how to deal with it.


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

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