SE4SafeML@SIGSOFT FSE

Publications

2023

Sheng Wong, Scott Barnett, Jessica Rivera-Villicana, Anj Simmons, Hala Abdelkader, Jean-Guy Schneider, Rajesh Vasa
MLGuard: Defend Your Machine Learning Model! SE4SafeML@SIGSOFT FSE (2023)
Mara Downing, Tevfik Bultan
The Case for Scalable Quantitative Neural Network Analysis. SE4SafeML@SIGSOFT FSE (2023)
Muhammad Usman, Youcheng Sun, Divya Gopinath, Corina S. Pasareanu
Rule-Based Testing of Neural Networks. SE4SafeML@SIGSOFT FSE (2023)
Proceedings of the 1st International Workshop on Dependability and Trustworthiness of Safety-Critical Systems with Machine Learned Components, SE4SafeML 2023, San Francisco, CA, USA, 4 December 2023 SE4SafeML@SIGSOFT FSE (2023)
Waris Gill, Ali Anwar, Muhammad Ali Gulzar
FedDefender: Backdoor Attack Defense in Federated Learning. SE4SafeML@SIGSOFT FSE (2023)
Sumon Biswas, Yining She, Eunsuk Kang
Towards Safe ML-Based Systems in Presence of Feedback Loops. SE4SafeML@SIGSOFT FSE (2023)
Hossein Mohasel Arjomandi, Reyhaneh Jabbarvand
Interpretable On-the-Fly Repair of Deep Neural Classifiers. SE4SafeML@SIGSOFT FSE (2023)