University of Cambridge > Talks.cam > Isaac Newton Institute Seminar Series > Does data interpolation contradict statistical optimality?

  Browse A-Z

Log in

University Account External (via Google)

🔐 Log In

Information on

Subscribing to talksdetails Finding a talkdetails Adding a talkdetails Disseminating talksdetails Help and Documentationdetails

ℹ️ Information

Does data interpolation contradict statistical optimality?

Download to your calendar using vCal

If you have a question about this talk, please contact INI IT .

STSW04 - Future challenges in statistical scalability

We exhibit estimators that interpolate the data, and yet achieve optimal rates of convergence for the problems of nonparametric regression and prediction with square loss. This curious observation goes against the usual intuition that a good statistical procedure should forego the exact fit to data in favor of a more smooth representation. A motivation for this work is the recent focus within the machine learning community on the out-of-sample performance of neural networks. These flexible models are typically trained to fit the data exactly (either in their sign or in the actual value), and yet they have good prediction behaviour. This talk is based on joint work with Misha Belkin and Sasha Rakhlin.

This talk is part of the Isaac Newton Institute Seminar Series series.

This talk is included in these lists:

Note that ex-directory lists are not shown.

Other lists

Castelreagh room, St. John's College Miseq Seminar Average on weekdays: 9209.36872146 kWh

Other talks

External Seminar - Hilde Nelissen TBC Morning Tea and Coffee Title to be confirmed Fairy Tales FILM: One With The Whale Coming soon
 

© 2006-2025 Talks.cam, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity