| M. Ajtai, T. Jayram, R. Kumar, and D. Sivakumar. Approximate counting of inversions in a data stream. Proceedings of the 34th Annual Symposium on Theory of Computing, 2002. |
....model. A data stream algorithm makes a few passes (usually one) over its input and is charged for the amount of read write workspace it uses. Using randomization and approximation, space e#cient data stream algorithms have been developed for many problems [AMS99, FKSV02, GMMO00, Ind00, GGI 02, AJKS02] The data stream model generalizes the restrictive read once oblivious branching program model for which strong lower bounds are known [Bry86, Weg87] however, since data stream algorithms are allowed to be both probabilistic and approximate, proving space lower bounds for natural problems is ....
M. Ajtai, T. S. Jayram, R. Kumar, and D. Sivakumar. Approximate counting of inversions in a data stream. In Proceedings of the 34th Annual ACM Symposium on Theory of Computing (STOC), pages 370--379, 2002.
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M. Ajtai, T. Jayram, R. Kumar, and D. Sivakumar. Approximate counting of inversions in a data stream. Proceedings of the 34th Annual Symposium on Theory of Computing, 2002.
No context found.
M. Ajtai, T.S. Jayram, R. Kumar, and D. Sivakumar. Approximate counting of inversions in a data stream. In 34th ACM Symposium on Theory of Computing, Montral, Qubec, Canada, 2002.
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Miklos Ajtai, T. S. Jayram, Ravi Kumar, and D. Sivakumar. Approximate counting of inversions in a data stream. In Proceedings of the ACM Symposium on Theory of Computing (STOC), 2002.
No context found.
Miklos Ajtai, T.S. Jayram, Ravi Kumar, and D. Sivakumar. Approximate counting of inversions in a data stream. In 34th ACM Symposium on Theory of Computing, Montral, Qubec, Canada, 2002.
No context found.
M. Ajtai, T.S. Jayram, R. Kumar, and D. Sivakumar. Approximate counting of inversions in a data stream. In 34th ACM Symposium on Theory of Computing, Montral, Qubec, Canada, 2002.
No context found.
Miklos Ajtai, T. S. Jayram, Ravi Kumar, and D. Sivakumar. Approximate counting of inversions in a data stream. In Proceedings of the ACM Symposium on Theory of Computing (STOC), 2002.
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