AI RESEARCH

Accurate and Scalable Matrix Mechanisms via Divide and Conquer

arXiv CS.LG

ArXi:2604.00868v1 Announce Type: cross Matrix mechanisms are often used to provide unbiased differentially private query answers when publishing statistics or creating synthetic data. Recent work has developed matrix mechanisms, such as ResidualPlanner and Weighted Fourier Factorizations, that scale to high dimensional datasets while providing optimality guarantees for workloads such as marginals and circular product queries. They operate by adding noise to a linearly independent set of queries that can compactly represent the desired workloads.