1.4k citations · 1.5k across the 9 of their papers we have counts for
4 papers · 2 filters
Practical Federated Gradient Boosting Decision Trees
Qinbin Li, Zeyi Wen, Bingsheng He
Gradient Boosting Decision Trees (GBDTs) have become very successful in recent years, with many awards in machine learning and data mining competitions. There have been several rec…
Adaptive Kernel Value Caching for SVM Training
Qinbin Li, Zeyi Wen, Bingsheng He
Support Vector Machines (SVMs) can solve structured multi-output learning problems such as multi-label classification, multiclass classification and vector regression. SVM training…
Privacy-Preserving Gradient Boosting Decision Trees
Qinbin Li, Zhaomin Wu, Zeyi Wen +1
The Gradient Boosting Decision Tree (GBDT) is a popular machine learning model for various tasks in recent years. In this paper, we study how to improve model accuracy of GBDT whil…
A Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection
Qinbin Li, Zeyi Wen, Zhaomin Wu +5
Federated learning has been a hot research topic in enabling the collaborative training of machine learning models among different organizations under the privacy restrictions. As…