Huaming Rao

Appraisal slashes the computational cost of privacy-preserving record linkage, making it feasible to screen 850x more records than existing systems when identifying potential data collaboration partners.

Training GBDTs on vertically partitioned data doesn't have to leak which records are shared: this new protocol hides record IDs while maintaining competitive efficiency.