A theoretical framework for analyzing the explainability capabilities of GAMs using computational complexity.

We investigate the computational complexity of finding local solutions for many contrastive learning settings based on triplet constraints (anchor-positive-negative paradigm), and we prove that reaching local optima cannot be done in polynomial time.