VF <sup>2</sup> Boost: Very Fast Vertical Federated Gradient Boosting for Cross-Enterprise Learning
Fangcheng Fu, Yingxia Shao, Lele Yu, Jiawei Jiang, Huanran Xue, Yangyu Tao, Bin Cui
Abstract
With the ever-evolving concerns on privacy protection, vertical federated learning (FL), where participants own non-overlapping features for the same set of instances, is becoming a heated topic since it enables multiple enterprises to strengthen the machine learning models collaboratively with privacy guarantees. Nevertheless, to achieve privacy preservation, vertical FL algorithms involve complicated training routines and time-consuming cryptography operations, leading to slow training speed.
Topics & Concepts
Boosting (machine learning)Computer scienceFederated learningCryptographyGradient boostingTraining setSet (abstract data type)Artificial intelligenceComputer securityProgramming languageRandom forestPrivacy-Preserving Technologies in DataCryptography and Data SecurityStochastic Gradient Optimization Techniques