Oral Talk
in
Workshop: Regulatable ML: Towards Bridging the Gaps between Machine Learning Research and Regulations
Oral Presentations
Abstract:
2 short talks in this session:
Learning from Label Proportions: Bootstrapping Supervised Learners via Belief Propagation by Shreyas Havaldar, Navodita Sharma, Shubhi Sareen, Karthikeyan Shanmugam, Aravindan Raghuveer
Towards a Post-Market Monitoring Framework for Machine Learning-based Medical Devices: A case study by Jean Feng, Adarsh Subbaswamy, Alexej Gossmann, Harvineet Singh, Berkman Sahiner, Mi-Ok Kim, Gene Pennello, Nicholas Petrick, Romain Pirracchio, Fan Xia
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