AINeutralarXiv – CS AI · 6h ago6/10
🧠
Interpretability-Guided Bi-objective Optimization: Aligning Accuracy and Explainability
Researchers introduce Interpretability-Guided Bi-objective Optimization (IGBO), a framework that trains machine learning models to balance accuracy with explainability by encoding feature importance hierarchies as directed acyclic graphs and using Temporal Integrated Gradients to measure feature contributions. The approach provides statistical guarantees for model interpretability while maintaining convergence properties.