Towards fair and decentralized federated learning system for gradient boosting decision trees

HIGHLIGHTS

• who: Gradient Boosting Decision Trees and colleagues from the Guangxi Key Lab of Multi-source Information Mining and Security, Guangxi Normal University, Guilin, China have published the paper: Towards Fair and Decentralized Federated Learning System for Gradient Boosting Decision Trees, in the Journal: Security and Communication Networks 0.28 of 21/06/2022
• what: The authors propose a novel federated GBDT scheme based on the blockchain which can achieve constant communication overhead and good model performance and quantify the contribution of each party. In response to the above challenges, the authors propose a closedloop federated . . .
  

   

  

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