[visionlist] SAVE THE DATE: EURASIP JIVP Webinar “Inferential Machine Learning: Towards Human-collaborative Foundation Models” (13 March 2025)

[Giuseppe Valenzise]

(Apologies if you receive multiple copies of this message)

Our next 1-hour webinar will take place Thursday, 13 March at 15:00 CET with Prof. Ghassan AlRegib (Georgia Institute of Technology, USA).

RSVP here to join: https://cassyni.com/events/Sn2yzuRyVG4SEUw8gn3wiV?cb=functi 

Title: Inferential Machine Learning: Towards Human-collaborative Foundation Models

Abstract: Neural network driven applications like ChatGPT suffer from hallucinations where they confidently provide inaccurate information. A funda- mental reason for this inaccuracy is the feed-forward nature of inductive decisions taken by neural networks. Such decisions are a result of training schemes that do not allow networks to deviate from and creatively abduce reasons at inference. With the advent of foundation models that are adapted across applications and data, humans can directly intervene and prompt vision-language foundation models. However, without understanding the operational limits of the underlying networks, human interventions often lead to unfair, inaccurate, hallucinated and unintelligible outputs. These outputs undermine the trust in foundation models, thereby causing roadblocks to their adoption in everyday lives. In this talk, we review systematic ways to analyze and understand human interventions in neural network functionality at inference. Specifically, we show that a human-AI collaborative environment via inferential machine learning techniques is a promising endeavor.

Bio: Prof. AlRegib is currently the John and Marilu McCarty Chair Professor in the School of Electrical and Computer Engineering at the Georgia Institute of Technology. In the Omni Lab for Intelligent Visual Engineering and Science (OLIVES), he and his group work on robust and interpretable machine learning algorithms, uncertainty and trust, and human in the loop algorithms. The group has demonstrated their work on a wide range of applications such as Autonomous Systems, Medical Imaging, and Subsurface Imaging. The group is interested in advancing the fundamentals as well as the deployment of such systems in real-world scenarios. He has been issued several U.S. patents and invention disclosures. He is a Fellow of the IEEE. Prof. AlRegib is active in the IEEE. He served on the editorial board of several transactions and served as the TPC Chair for ICIP 2020, ICIP 2024, and GlobalSIP 2014. He was area editor for the IEEE Signal Processing Magazine. In 2008, he received the ECE Outstanding Junior Faculty Member Award. In 2017, he received the 2017 Denning Faculty Award for Global Engagement. He received the 2024 ECE Distinguished Faculty Achievement Award at Georgia Tech. He and his students received the Best Paper Award in ICIP 2019 and the 2023 EURASIP Best Paper Award for Image communication Journal. In addition, one of their papers is the best paper runner-up at BigData 2024. In 2024, he co-founded the AI Makerspace at Georgia Tech, where any student and any community member can access and utilize AI regardless of their background.

We look forward to seeing you at this webinar.

Kind regards,

Giuseppe Valenzise

—
__________________________________________
Dr. Giuseppe Valenzise
CNRS Researcher
Laboratoire des Signaux et Systèmes (L2S, UMR 8506)
CNRS - CentraleSupelec - Université Paris-Saclay
3, rue Joliot Curie
91192 Gif-sur-Yvette Cedex, France
https://l2s.centralesupelec.fr/u/valenzise-giuseppe/

General Chair - ICME 2025 <https://2025.ieeeicme.org/>

Chair of the IEEE SPS Multimedia Signal Processing Technical Committee (MMSP TC) <https://signalprocessingsociety.org/community-involvement/multimedia-signal-processing/mmsp-tc-home>

Editor in Chief EURASIP Journal on Image and Video Processing <https://jivp-eurasipjournals.springeropen.com/>





~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
“Immersive Video Technologies”
https://www.elsevier.com/books/immersive-video-technologies/valenzise/978-0-323-91755-1


-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://visionscience.com/pipermail/visionlist_visionscience.com/attachments/20250309/7e8a6967/attachment-0001.html>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: signature_banner.png
Type: image/png
Size: 160520 bytes
Desc: not available
URL: <http://visionscience.com/pipermail/visionlist_visionscience.com/attachments/20250309/7e8a6967/attachment-0001.png>