1 citations · 1 across the 1 of their papers we have counts for
2 papers
cs.CR2020★ 1 cited
Secure Collaborative Training and Inference for XGBoost
Andrew Law, Chester Leung, Rishabh Poddar +6
In recent years, gradient boosted decision tree learning has proven to be an effective method of training robust models. Moreover, collaborative learning among multiple parties has…
cs.CR2019
Helen: Maliciously Secure Coopetitive Learning for Linear Models
Wenting Zheng, Raluca Ada Popa, Joseph E. Gonzalez +1
Many organizations wish to collaboratively train machine learning models on their combined datasets for a common benefit (e.g., better medical research, or fraud detection). Howeve…