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[The 67th TrustML Young Scientist Seminar]

Tue, 18 Apr 2023 17:00 - 18:00 JST
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-Passcode TcX7YKB5Db -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.

Description

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 March to April. 2023.

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 67th Seminar】


Date and Time: April 18th 5:00 pm - 6:00 pm(JST)

Speaker: Yuki Funabiki (Sony Group Corporation JAPAN)
Title: Adversarial Attacks for Tabular Data: Application to Fraud Detection and Imbalanced Data

Short Abstract
Many researchers have focused on adversarial scenarios for machine learning, and adversarial examples are a major one among them. This talk will discuss adversarial examples against machine learning models using tabular data. This use case corresponds to fraud detection in financial transaction systems such as banking and online shopping, a scenario that is closer to real business scenarios than attacks on images. Challenges and solutions for applying the algorithm for generating adversarial examples developed in the attack on images to tabular data will be described.

Bio:
Yuki Funabiki received the B.E. and M.E. degrees from Kobe University, Japan, in 2017 and 2019. Since 2019, he has been a research scientist at the Sony Corporation, Japan. His research current interests include adversarial machine learning, image authentication and cryptography.


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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