Sarus just released DP-XGBoost


XGBoost is one of the most popular gradient boosted trees library and is featured in many winning solutions on Kaggle competitions. It's written in C and useable in many languages: Python, R, Java, Julia, or Scala. It can run on major distributed environments (Kubernetes, Apache Spark, or Dask) to handle datasets with billions of examples. XGBoost is often used to train models on sensitive data. Since it comes with no privacy guarantee, one can show that personal information may remain in the model weights.

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