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[The 45th TrustML Young Scientist Seminar]

2022-12-13(火)17:00 - 18:00 JST
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-Passcode sBQ5r635NF -Time Zone:JST -The seats are available on a first-come-first-served basis. -When the seats are fully booked, we may stop accepting applications. -Simultaneous interpretation will not be available.

詳細

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 Nov. to Dec. 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 45th Seminar】


Date and Time: Dec. 13th 5:00 pm - 6:00 pm(JST)

Venue: Zoom webinar

Language: English

Speaker: Teresa Yeo (EPFL)
Title: Robustness via Cross Domain Ensembles
Short Abstract
Neural networks are able to learn complex functions on in-distribution data. However, their predictions are unreliable under distribution shifts, i.e. they are not robust. In this talk, I will present a method for making neural network predictions robust to shifts from the training data distribution. The proposed method is based on making predictions via a diverse set of cues and ensembling them into one strong prediction. The merging is done in a straightforward but principled manner based on the uncertainty associated with each prediction. Evaluations performed on multiple tasks and datasets under a wide range of shifts demonstrate that the proposed method is more robust than the baselines.


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.


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