革新知能統合研究センター

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.
TrustML YSS

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

【The 34th Seminar】

Date and Time: Oct. 6th 10:00 am – 11:00 am(JST)

Venue: Zoom webinar

Language: English

Speaker: Sharon Y. Li (University of Wisconsin Madison)
Title: Challenges and Opportunities in Out-of-distribution Detection
Short Abstract
The real world is open and full of unknowns, presenting significant challenges for machine learning (ML) systems that must reliably handle diverse, and sometimes anomalous inputs. Out-of-distribution (OOD) uncertainty arises when a machine learning model sees a test-time input that differs from its training data, and thus should not be predicted by the model. As ML is used for more safety-critical domains, the abilities to handle out-of-distribution data are central in building open-world learning systems. In this talk, I will talk about challenges, research progress and and future opportunities in detecting OOD samples for safe and reliable predictions in an open world.

All participants are required to agree with the AIP Seminar Series Code of Conduct.
Please see the URL below.
https://aip.riken.jp/event-list/termsofparticipation/?lang=en

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.