The thesis identifies theoretical, empirical, and conceptual flaws in offline fairness measures for recommender systems and contributes new evaluation methods and practical guidelines.
Pazzani and Daniel Billsus.Content-Based Recommendation Sys- tems, pages 325–341
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Personalized deep learning models on multimodal physiological signals from an Empatica E4 sensor achieve 92.68% accuracy for driver state classification in real-world automated driving, compared to 54% for generalized models across four drivers.
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