The Computer-Based Patient Record: An Essential Technology for Health Care
The Computer-Based Patient Record: An Essential Technology for Health Care
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
k-anonymity: a model for protecting privacy
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Privacy: A Machine Learning View
IEEE Transactions on Knowledge and Data Engineering
Ruling Out PTAS for Graph Min-Bisection, Densest Subgraph and Bipartite Clique
FOCS '04 Proceedings of the 45th Annual IEEE Symposium on Foundations of Computer Science
On the complexity of optimal K-anonymity
PODS '04 Proceedings of the twenty-third ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
The hospitals/residents problem with quota lower bounds
ESA'11 Proceedings of the 19th European conference on Algorithms
On the inapproximability of minimizing cascading failures under the deterministic threshold model
Information Processing Letters
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Let (L, *) be a semilattice, and let c : L → [0,∞) be monotone and increasing on L. We state the Minimum Join problem as: given size n sub-collection X of L and integer k with 1 ≤ k ≤ n, find a size k sub-collection (x'1, x'2, . . ., x'k) of X that minimizes c(x'1 * x'2 * ... * x'k). If c(a * b) ≤ c(a) + c(b) holds, we call this the Minimum Subadditive Join (MSJ) problem and present a greedy (k - p + 1)-approximation algorithm requiring O((k-p)n+ np) joins for constant integer 0 p ≤ k. We show that the MSJ Minimum Coverage problem of selecting k out of n finite sets such that their union is minimal is essentially as hard to approximate as the Maximum Balanced Complete Bipartite Subgraph (MBCBS) problem. The motivating by-product of the above is that the privacy in databases related k-ambiguity problem over L with subadditive information loss can be approximated within k - p, and that the k-ambiguity problem is essentially at least as hard to approximate as MBCBS.