The Parameterized Complexity of Network Microaggregation
Autoři
Rok
2023
Publikováno
Proceedings of the 37th AAAI Conference on Artificial Intelligence. Menlo Park: AAAI Press, 2023. p. 6262-6270. ISSN 2159-5399.
Typ
Stať ve sborníku
Pracoviště
Anotace
Microaggregation is a classical statistical disclosure control technique which requires the input data to be partitioned into clusters while adhering to specified size constraints. We provide novel exact algorithms and lower bounds for the task of microaggregating a given network while considering both unrestricted and connected clusterings, and analyze these from the perspective of the parameterized complexity paradigm. Altogether, our results assemble a complete complexity-theoretic picture for the network microaggregation problem with respect to the most natural parameterizations of the problem, including input-specified parameters capturing the size and homogeneity of the clusters as well as the treewidth and vertex cover number of the network.