Soft Voting for Policy-Aware Private Data Synthesis
BF-Soft proposes a temperature-smoothed soft vote to reduce noise in private data synthesis using policy graphs. It creates a sensitivity bound independent of candidate count and computable beforehand, showing noise reduction when policies protect numeric or ordinal attributes with narrow thresholds, especially at strong privacy budgets.