Algorithms: design techniques and analysis
Algorithms: design techniques and analysis
Algorithms for facility location problems with outliers
SODA '01 Proceedings of the twelfth annual ACM-SIAM symposium on Discrete algorithms
Protecting Respondents' Identities in Microdata Release
IEEE Transactions on Knowledge and Data Engineering
Location Privacy in Pervasive Computing
IEEE Pervasive Computing
Constrained K-means Clustering with Background Knowledge
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Clustering with Instance-level Constraints
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Machine Learning
On the complexity of optimal K-anonymity
PODS '04 Proceedings of the twenty-third ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Correlation clustering with a fixed number of clusters
SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
Mondrian Multidimensional K-Anonymity
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
\ell -Diversity: Privacy Beyond \kappa -Anonymity
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Achieving anonymity via clustering
Proceedings of the twenty-fifth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Injecting utility into anonymized datasets
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
(α, k)-anonymity: an enhanced k-anonymity model for privacy preserving data publishing
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Anatomy: simple and effective privacy preservation
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Approximate algorithms for K-anonymity
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
M-invariance: towards privacy preserving re-publication of dynamic datasets
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Intractability and clustering with constraints
Proceedings of the 24th international conference on Machine learning
Fast data anonymization with low information loss
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Aggregating inconsistent information: Ranking and clustering
Journal of the ACM (JACM)
Proceedings of the forty-first annual ACM symposium on Theory of computing
On the complexity of differentially private data release: efficient algorithms and hardness results
Proceedings of the forty-first annual ACM symposium on Theory of computing
Large-Scale Deduplication with Constraints Using Dedupalog
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Combinatorial Optimization: Theory and Algorithms
Combinatorial Optimization: Theory and Algorithms
The hardness and approximation algorithms for l-diversity
Proceedings of the 13th International Conference on Extending Database Technology
ICALP'10 Proceedings of the 37th international colloquium conference on Automata, languages and programming
ICDT'05 Proceedings of the 10th international conference on Database Theory
ICALP'10 Proceedings of the 37th international colloquium conference on Automata, languages and programming
On the complexity of the l-diversity problem
MFCS'11 Proceedings of the 36th international conference on Mathematical foundations of computer science
Partitioning into colorful components by minimum edge deletions
CPM'12 Proceedings of the 23rd Annual conference on Combinatorial Pattern Matching
A Knowledge Model Sharing Based Approach to Privacy-Preserving Data Mining
Transactions on Data Privacy
Matroid and knapsack center problems
IPCO'13 Proceedings of the 16th international conference on Integer Programming and Combinatorial Optimization
The l-Diversity problem: Tractability and approximability
Theoretical Computer Science
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We consider the clustering with diversity problem: given a set of colored points in a metric space, partition them into clusters such that each cluster has at least l points, all of which have distinct colors. We give a 2-approximation to this problem for any l when the objective is to minimize the maximum radius of any cluster. We show that the approximation ratio is optimal unless P = NP, by providing a matching lower bound. Several extensions to our algorithm have also been developed for handling outliers. This problem is mainly motivated by applications in privacy-preserving data publication.