Sampling algorithms for differential batch retrieval problems (extended abstract)

Willard, Dan E.

doi:10.1007/3-540-13345-3_48

Cited by 8 publications

(4 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Once again, we remind the reader that he may wish to examine two other equally important conference papers recently completed by Willard [Wi83,Wi84].…”

Section: Extensions Mmentioning

confidence: 99%

“…We suspect that randomized algorithms are likely to become an increasingly major topic in computer science, and recommend [Wi83,Wi84] in the strongest terms to the reader because we think the interaction between these two papers will eventually be seen as a classic result.…”

Section: Introductionmentioning

confidence: 98%

“…The latter paper [Wi84] considers applications where several batch retrieval algorithms are available for performing a particular task and no one of these procedures is the most efficient for all possible statistical distributiosn of data.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Log-logarithmic protocols for resolving ethernet and semaphore conflicts

Willard¹

1984

Proceedings of the Sixteenth Annual ACM Symposium on Theory of Computing - STOC '84

Self Cite

View full text Add to dashboard Cite

show abstract

“…Once again, we remind the reader that he may wish to examine two other equally important conference papers recently completed by Willard [Wi83,Wi84].…”

Section: Extensions Mmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 98%

See 1 more Smart Citation

Log-logarithmic protocols for resolving ethernet and semaphore conflicts

Willard¹

1984

Proceedings of the Sixteenth Annual ACM Symposium on Theory of Computing - STOC '84

Self Cite

View full text Add to dashboard Cite

show abstract

“…The realization that no article in the previous database literature had studied extensively the trade-off between sample size and the accuracy of a dawned first on me in the Winter of 1981, approximately three years before I presented the conference version of this paper [35]. In 1981.…”

Section: Acknowledgmentsmentioning

confidence: 99%

Optimal sample cost residues for differential database batch query problems

Willard

1991

J. ACM

Self Cite

View full text Add to dashboard Cite

In many computing applications, there are several equi~alent algorithms capable of performmg a particular task, and no one is the most eflicient under all statistical dntrrbutions of the data. In such contexts, a good heunstlc is to take a sample of the database and use it to guess which procedure is likely to be the most efticlent This paper defines the very geneml notion of a differentiable query problem and shows that the Ideal sample size for guessing the optimal choice of algorithm is CJ(NZ13) for all differential problems involving approximately N executing steps. ACM 0004-541 I/91/010()-()1()4 $OI,5f)

show abstract

Statistical Databases

Srivastava¹,

Ngo²

1999

Wiley Encyclopedia of Electrical and Electronics Engineering

View full text Add to dashboard Cite

The sections in this article are Requirements of Statistical Databases Statistical Data Models and Metadata Statistical Query Languages Physical Database Design and Index Structures for Statistical Operations Query Processing and Optimization Sampling and Its Role in Statistical Databases Statistical Database Security Other Issues Conclusion

show abstract

Sampling algorithms for differential batch retrieval problems (extended abstract)

Cited by 8 publications

References 19 publications

Log-logarithmic protocols for resolving ethernet and semaphore conflicts

Log-logarithmic protocols for resolving ethernet and semaphore conflicts

Optimal sample cost residues for differential database batch query problems

Statistical Databases

Contact Info

Product

Resources

About