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H. Mamman

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Conference Open access 2026

From Accuracy to Reliability: A Trust-Centric Machine Learning Framework for Safe Decision-Making

A trust-centric framework that integrates ensemble-based uncertainty estimation, maximum mean discrepancy (MMD) shift detection, a dependability signal, and safety-aware decision logic to prioritize reliable actions over raw predictive confidence is proposed.

Yusuf Surajo, S. Basri, A. Balogun et al. · 0 citations
#software testing Open access Aug 2026

FIFT: Feature Importance-Guided Fairness Testing for machine learning software

Results indicate that global feature importance, used as an active search signal rather than a post-hoc diagnostic, improves both the effectiveness and the efficiency of individual fairness testing.

H. Mamman, Abdullateef Oluwagbemiga Balogun, Mustapha Maidawa et al. · 0 citations