Ents: An Efficient Three-party Training Framework for Decision Trees by Communication Optimization

no code implementations • 12 Jun 2024 • Guopeng Lin, Weili Han, Wenqiang Ruan, Ruisheng Zhou, Lushan Song, Bingshuai Li, Yunfeng Shao

However, existing multi-party training frameworks for decision trees demonstrate communication inefficiency due to the following issues: (1) They suffer from huge communication overhead in securely splitting a dataset with continuous attributes.

SoK: Training Machine Learning Models over Multiple Sources with Privacy Preservation

no code implementations • 6 Dec 2020 • Lushan Song, Guopeng Lin, Jiaxuan Wang, Haoqi Wu, Wenqiang Ruan, Weili Han

At first, we define the problem of Training machine learning Models over Multiple data sources with Privacy Preservation (TMMPP for short).

BIG-bench Machine Learning Federated Learning +1