Qian Bo
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126
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Crypto×1AI×1
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2026
Practical Anonymous Two-Party Gradient Boosting Decision Tree
This paper introduces a novel, efficient protocol for training Gradient Boosting Decision Trees (GBDT) on vertically partitioned data held by two mutually distrustful parties while ensuring complete anonymity by hiding record identifiers.
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cs.CRcs.AIRecentMay 26, 2026
Practical Anonymous Two-Party Gradient Boosting Decision Tree
Huang Chenyu, Zhang Fan, Du Minxin, Chow Sherman SM +5 more
This paper introduces a novel, efficient protocol for training Gradient Boosting Decision Trees (GBDT) on vertically partitioned data held by two mutually distrustful parties while ensuring complete a…
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