2026
TT-Sparse: Learning Sparse Rule Models with Differentiable Truth Tables
ICML 2026poster
Interpretable machine learning is essential in high-stakes domains where decision-making requires accountability, transparency, and trust. While rule-based models offer global and exact interpretability, learning rule sets that achieve high performance while maintaining low complexity to be human un…