AI Seminar-On Robustness and Generative Modeling

Speaker: Iacopo Masi, Sapienza University of Rome

Talk Title: On Robustness and Generative Modeling

Abstract: The bloom of AI capabilities and their practical implication in our lives raised concerns regarding AI's robustness to an adversary. A way to improve the robustness of the prediction is adversarial training (AT), which trains the predictor on adversarial data. Although AT is mainly associated with discriminative models, in this talk, I will show how we can shed light on some mysterious behaviors using generative modeling. By reinterpreting a robust discriminative classifier as an Energy-based Model (EBM), we offer a new take on the dynamics of adversarial training. On the ground of our thorough analysis, we present new theoretical and practical results that show how interpreting AT energy dynamics unlocks a better understanding of (i) robust overfitting, (ii) distinct features of different AT methods, such as SAT and TRADES (iii) their generative capabilities; also offering a simple process to lift these capabilities without training for generative modeling. In the last part of the talk, I will discuss how we can use off-the-shelf robust classifiers to help generative modeling by inverting them.    REMINDER: If you do not have access to the 11th Floor, please check in at the main reception desk on 10th floor and someone will escort you to the conference room location prior to the start of the talk. Meeting hosts only admit guests that they know to the Zoom meeting. Hence, you’re highly encouraged to use your USC account to sign into Zoom. If you’re an outside visitor, please provide your: Full Name, Title and Name of Workplace to (aiseminars-poc(at)isi.edu) beforehand so we’ll be aware of your attendance.  REGISTRATION IS REQUIRED https://usc.zoom.us/webinar/register/WN_ontXffySQ7mOaBn75fp8xg Zoom Webinar Info:  https://usc.zoom.us/s/95834774243?pwd=U1k0S3A5Y0VERTZCM3RuQnhvdEJwUT09 Meeting ID: 958 3477 4243 Passcode: 945662

Biography: Dr. Iacopo Masi is an Associate Professor in the Computer Science Department at Sapienza, University of Rome. He is also the Principal Investigator and founder of the OmnAI Lab. Until August 2022, he held the position of Adjunct Research Assistant Professor in the Computer Science Department at the University of Southern California (USC). Previously, Dr. Masi was a Research Assistant Professor and Research Computer Scientist at the USC Information Sciences Institute (ISI). He has served as an Area Chair for several computer vision conferences (WACVs, ICCV'21, ECCV'22, CVPR'24) and is an Associate Editor for The Visual Computer - International Journal of Computer Graphics. Additionally, he organized an International Workshop on Human Identification at ICCV'17, co-organized the Unlearning and Model Editing (U&Me) workshop at ECCV'24, and is a general chair for ICIAP'25. In 2018, Dr. Masi was honored with the prestigious Rita Levi Montalcini Award by the Italian government. His primary research interests revolve around the intersection of machine learning, computer vision, and biometrics. Currently, he is exploring various interconnected lines of research, including adversarial robustness, proactive defense against image manipulation, inverse problems, and generative AI in both the vision and NLP domains. To learn more, visit https://omnai.di.uniroma1.it and https://iacopomasi.github.io"         

Host: Fred Morstatter and Craig Knoblock

More Info: https://www.isi.edu/events/4998/ai-seminar-on-robustness-and-generative-modeling/

Webcast: https://www.youtube.com/watch?v=dY9d2oRkU3w

Location: Information Science Institute (ISI) - Conf Rms #1135-37 and Virtual

WebCast Link: https://www.youtube.com/watch?v=dY9d2oRkU3w

Audiences: Everyone Is Invited

Contact: Pete Zamar

Event Link: https://www.isi.edu/events/4998/ai-seminar-on-robustness-and-generative-modeling/