2025
Enhancing Performance of Explainable AI Models with Constrained Concept Refinement
ICML 2025poster
The trade-off between accuracy and interpretability has long been a challenge in machine learning (ML). This tension is particularly significant for emerging *interpretable-by-design* methods, which aim to redesign ML algorithms for trustworthy interpretability but often sacrifice accuracy in the pr…