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cs.AI2026
Algorithmic drift in generative adaptive learning
Firuz Kamalov, Hana Sulieman, Ahmed El Sayed +2
Generative artificial intelligence promises to democratize personalized tutoring, yet the longitudinal stability of adaptive systems remains under-theorized. Current ethical discou…
cs.LG2026
Theoretical Convergence of SMOTE-Generated Samples
Firuz Kamalov, Hana Sulieman, Witold Pedrycz
Imbalanced data affects a wide range of machine learning applications, from healthcare to network security. As SMOTE is one of the most popular approaches to addressing this issue,…