Tentative Program

Accepted Papers

The following papers are accepted for the workshop proceedings:
• "FedDefender: Backdoor Attack Defense in Federated Learning"
  Waris Gill, Ali Anwar, Muhammad Ali Gulzar
• "Interpretable On-the-Fly Repair of Deep Neural Classifiers"
  Hossein Mohasel Arjomandi, Reyhaneh Jabbarvand
• "MLGuard: Defend Your Machine Learning Model!"
  Sheng Wong, Scott Barnett, Jessica Rivera-Villicana, Anj Simmons, Hala Abdelkader, Jean-Guy Schneider, Rajesh Vasa
• "Rule-based Testing of Neural Networks"
  Muhammad Usman, Youcheng Sun, Divya Gopinath, Corina Pasareanu
• "Towards Safe ML-based Systems in the Presence of Feedback Loops"
  Sumon Biswas, Yining She, Eunsuk Kang
• "The Case for Scalable Quantitative Neural Network Analysis"
  Mara Downing, Tevfik Bultan

Additionally, we accepted the following presentations:

• "A Divide-and-Conquer Methodology for Testing and Improving Machine Learning Models"
  Lina Marsso, Nikita Dvornik, Marsha Chechik
• "Certifying Trustworthy Deep Learning Systems at Scale"
  Linyi Li
• "Finding Property Violations through Network Falsification: Challenges, Adaptations and Lessons Learned from OpenPilot"
  Meriel von Stein, Sebastian Elbam
• "Reliability of Machine Vision Components in Safety-critical Systems"
  Boyue Caroline Hu, Marsha Chechik