August 25, 2022 07:28


The TrustML Young Scientist Seminars (TrustML YSS) started from January 28, 2022.

The TrustML YSS is a video series that features young scientists giving talks and discoveries in relation with Trustworthy Machine Learning.

Timetable for the TrustML YSS online seminars from Sep. to Oct. 2022.

For more information please see the following site.

This network is funded by RIKEN-AIP’s subsidy and JST, ACT-X Grant Number JPMJAX21AF, Japan.

【The 28th Seminar】

Date and Time: September 1st 11:00 am – 12:00 pm(JST)

Venue: Zoom webinar

Language: English

Speaker: Yaodong Yu (University of California, Berkeley)
Title: Predicting Out-of-Distribution Error with the Projection Norm
Short Abstract
We propose a metric — Projection Norm — to predict a model’s performance on out-of-distribution (OOD) data without access to ground truth labels. Projection Norm first uses model predictions to pseudo-label test samples and then trains a new model on the pseudo-labels. The more the new model’s parameters differ from an in-distribution model, the greater the predicted OOD error. Empirically, our approach outperforms existing methods on both image and text classification tasks and across different network architectures. Theoretically, we connect our approach to a bound on the test error for overparameterized linear models. Furthermore, we find that Projection Norm is the only approach that achieves non-trivial detection performance on adversarial examples. Our code is available at

This is a joint work with Zitong Yang, Alexander Wei, Yi Ma, and Jacob Steinhardt.

All participants are required to agree with the AIP Seminar Series Code of Conduct.
Please see the URL below.

RIKEN AIP will expect adherence to this code throughout the event. We expect cooperation from all participants to help ensure a safe environment for everybody.

More Information

Date September 1, 2022 (Thu) 11:00 - 12:00