WilliamJonas08/Secure-Multi-Party-Computation

This project is a 4-year-old research artifact originating from a collaboration with Criteo. With only 6 stars and zero recent activity, it functions as a point-in-time evaluation rather than a living software tool. The Secure Multi-Party Computation (sMPC) and Federated Learning (FL) space has since moved toward significantly more robust, production-grade frameworks like Ant Group's SecretFlow, OpenMined's PySyft, or Google's TensorFlow Federated. While the Criteo connection suggests it may have addressed specific ad-tech constraints (e.g., high-cardinality features or specific attribution logic), the lack of community adoption and documentation makes it an easily reproducible or entirely obsolete reference compared to modern Privacy-Preserving Machine Learning (PPML) libraries.