Zero-Knowledge Proofs for Gradient Boosted Decision Trees

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Gradient boosted decision trees (GBDTs) are widely used for tabular data in finance, healthcare, and risk ssessment. As GBDT training and inference are increasingly outsourced, clients need to verify that models are trained as claimed and predictions are consistent with those models, while providers may need to keep training data and model parameters private. This makes zero-knowledge proofs for GBDT training and inference a natural solution. Existing approaches typically compile training cer