Title: There is plenty of room at the bottom: verification (and repair) of small-scale learning models
Abstract: With the growing popularity of machine learning, the quest for verifying data-driven models is attracting more and more attention, and researchers in automated verification are struggling to meet the scalability and expressivity demands imposed by the size and the complexity of state-of-the-art machine learning architectures. However, there are applications where relatively small-scale learning models are enough to achieve industry-standard performances, yet the issue of checking whether those models are reliable remains challenging. Furthermore, in these domains, verification is just half of the game: providing automated ways to repair models that are found to be faulty is also an important task in practice. In this talk, I will touch upon some research directions that I have pursued in the past decade, commenting the results and providing some connections with related efforts.
The inofficial proceedings with all abstracts can be found here.
The discussion document is here.
Important dates:
In case of any questions, please contact the organizer Jan Kretinsky at <name>.<surname>@tum.de
Looking forward to seeing you LiVe in Munich!