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cs.LG2026
Evaluating Model Retraining under Drift: Paired Comparisons of Cumulative Subgroup Disparity
Aaron Ceross
Choosing when to retrain a deployed classifier requires assessing subgroup error rates across the sequence of models used, including periods between updates. We compare complete sc…
cs.LG2025
Toward Automated Regulatory Decision-Making: Trustworthy Medical Device Risk Classification with Multimodal Transformers and Self-Training
Yu Han, Aaron Ceross, Jeroen H. M. Bergmann
Accurate classification of medical device risk levels is essential for regulatory oversight and clinical safety. We present a Transformer-based multimodal framework that integrates…