Implement FALCON: Honest-Majority Maliciously Secure Framework for Private Deep Learning in SyMPC

FALCON is the current state-of-the-art Multiparty Computation (MPC) Framework for Private-Deep Learning(PDL).MPC allows mutually distrusting parties to jointly compute a function without revealing their private inputs beyond what is revealed by the output of the computation. PDL allows multiple parties to collaboratively train a Machine Learning model without revealing their private inputs. It also encompasses secure prediction.MPC is one of the privacy advocates for PDL.

The project aims to implement FALCON in the SyMPC library. It would greatly improve the performance of the SyMPC library for training and inference.