Edge-Private Matching Kernels Through Local Decoding
This research addresses computing maximum matchings and b-matchings in general graphs while protecting node and edge privacy. The authors developed techniques like arboricity-based sparsifiers to reduce graph complexity, allowing for approximate solutions under differential privacy constraints across central, local, and continual data release models.