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Mirror, Mirror, on the Wall, Who's the Fairest of Them All?
A **ang - Daedalus, 2024 - direct.mit.edu
Debates in AI ethics often hinge on comparisons between AI and humans: which is more
beneficial, which is more harmful, which is more biased, the human or the machine? These …
beneficial, which is more harmful, which is more biased, the human or the machine? These …
Deep learning pitfall: impact of novel ultrasound equipment introduction on algorithm performance and the realities of domain adaptation
M Blaivas, LN Blaivas, JW Tsung - Journal of Ultrasound in …, 2022 - Wiley Online Library
Objectives To test deep learning (DL) algorithm performance repercussions by introducing
novel ultrasound equipment into a clinical setting. Methods Researchers introduced …
novel ultrasound equipment into a clinical setting. Methods Researchers introduced …
Refining machine learning evaluation: statistical insights into model performance and fairness
M Soumm - 2024 - theses.hal.science
This thesis addresses limitations in machine learning evaluation methodologies by
introducing rigorous statistical approaches adapted from econometrics. Through …
introducing rigorous statistical approaches adapted from econometrics. Through …