Privacy-preserving machine learning enables the training of models on decentralized datasets without need to reveal data, both horizontal and vertically partitioned data. However, it relies specialized techniques algorithms perform necessary computations. The privacy preserving scalar product protocol, which dot vectors revealing them, is one popular example for its versatility. Unfortunately, ...