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Efficient algorithms for geometric optimization
Open accessAbstract
We review the recent progress in the design of efficient algorithms for various problems in geometric optimization. We present several techniques used to attack these problems, such as parametric searching, geometric alternatives to parametric searching, prune-and-search techniques for linear programming and related problems, and LP-type problems and their efficient solution. We then describe a wide range of applications of these and other techniques to numerous problems in geometric optimization, including facility location, proximity problems, statistical estimators and metrology, placement and intersection of polygons and polyhedra, and ray shooting and other query-type problems.
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Cites
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(2014) · Choice Reviews Online · doi:10.5860/choice.51-2713 · Cited by 4,651
Comparing images using the Hausdorff distance
Huttenlocher, D. P., Klanderman, G. A., & Rucklidge, W. J. (1993) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.232073 · Cited by 4,545
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(1997) · ACM SIGACT News · doi:10.1145/261342.571216 · Cited by 3,103
Automatic subspace clustering of high dimensional data for data mining applications
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Metadata
- Authors
- Agarwal, P. K., & Sharir, M.
- Venue
- ACM Computing Surveys
- Published
- 1998-12
- Volume
- 30
- Issue
- 4
- Pages
- 412-458
- ISSN
- 0360-0300 (ISSN-L)
- 1557-7341
- OpenAlex
- W2161779238
- Cited by
- 257
- References
- 81
- FWCI
- 6.14
- Type
- journal article
- Language
- en
- Open access
- bronze
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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