1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2026
Rank-Constrained Adaptation for Reliable Real-World Performance
Abinitha Gourabathina, Hyewon Jeong, Teya Bergamaschi +2
Deep learning models trained to optimize average accuracy often exhibit systematic failures on particular subpopulations. In real-world settings like healthcare, the subpopulations…
cs.LG2024★ 1 cited
MEDS-Tab: Automated tabularization and baseline methods for MEDS datasets
Nassim Oufattole, Teya Bergamaschi, Aleksia Kolo +4
Effective, reliable, and scalable development of machine learning (ML) solutions for structured electronic health record (EHR) data requires the ability to reliably generate high-q…