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cs.LG2026
Lumberjack: Better Differentially Private Random Forests through Heavy Hitter Detection in Trees
Christian Janos Lebeda, David Erb, Tudor Cebere +1
Random forests are widely used in fields involving sensitive tabular data, but existing approaches to enforcing differential privacy (DP) typically degrade performance to the point…
cs.LG2026
Model Agnostic Differentially Private Causal Inference
Christian Janos Lebeda, Mathieu Even, Aurélien Bellet +1
Estimating causal effects from observational data is essential in fields such as medicine, economics and social sciences, where privacy concerns are paramount. We propose a general…