Sunil Arya
David M. Mount
- 1.S. Arya and D. M. Mount. Approximate nearest neighbor queries in fixed dimensions. In Proceedings of the 4th A CM-SIAM Symposium on Discrete Algorithms, pages 271-280, 1993. Google Scholar
Digital Library
- 2.S. Arya and D. M. Mount. Algorithms for fast vector quantization. In J. A. Storer and M. Colin, editors, Proc. of DCC '93: Data Compression Conference, pages 381-390. IEEE Press, 1993.Google Scholar
- 3.S. Arya, D. M. Mount, N. S. Netanyahu, R. Silverman and A. Wu. An optimal algorithm for approximate nearest neighbor searching, in Proceedings of the 5th A CM-SIAM Symposium on Discrete Algorithms, pages 573-582, 1994. Google ScholarDigital Library
- 4.C. M. Bender and S. A. Orszag. Advanced mathematical methods for scientists and engineers. International series in pure and applied mathematics. McGraw-Hill, 1978.Google Scholar
- 5.J. L. Bentley. Multidimensional binary search trees used for associative searching. Communications of the A CM, 18(9):509-517, September 1975. Google ScholarDigital Library
- 6.K. L. Clarkson. An algorithm for approximate closest-point queries. In Proceedings of the l Oth Annual A CM Symposium on Computational Geometry, pages 160-164, 1994. Google ScholarDigital Library
- 7.J. G. Cleary. Analysis of an algorithm for fining nearest neighbors in Euclidean space. A CM Transactions on Mathematical Software, 5(2):183-192, June 1979. Google ScholarDigital Library
- 8.J. H. Friedman, J. L. Bentley, and R.A. Finkel. An algorithm for finding best matches in logarithmic expected time. ACM Transactions on Mathematical Software, 3(3):209-226, September 1977. Google ScholarDigital Library
- 9.A. Gersho and R. M. Gray. Vector Quantization and Signal Compression. Kluwer Academic, 1991. Google ScholarDigital Library
- 10.G. Goertzel and N. Tra}~. Some mathematical methods of physics. McGraw-Hill, 1960.Google Scholar
- 11.R. L. Rivest. On the optimality of Elias's algorithm for performing best-match searches. In Information Processing, pages 678-681. North HoUand Publishing Company, 1974.Google Scholar
- 12.R. L. Sprou11. Refinements to nearest-neighbor searching in k-dimensional trees. Algorithmica, 6, 1991.Google Scholar
- 13.T. Welch. Bounds on the information retrieval efficiency of static file structures. Technical Report 88, MIT, June 1971. Google ScholarDigital Library
Index Terms
- Accounting for boundary effects in nearest neighbor searching
Recommendations
Fast k-Nearest Neighbor Searching in Static Objects
The k-nearest neighbor searching is a classical problem that has been seriously studied, due to its many important applications. The paper proposes an efficient algorithm to search the k-nearest neighbors for static objects. Since locations of static ...
Nearest neighbor searching under uncertainty II
PODS '13: Proceedings of the 32nd ACM SIGMOD-SIGACT-SIGAI symposium on Principles of database systemsNearest-neighbor (NN) search, which returns the nearest neighbor of a query point in a set of points, is an important and widely studied problem in many fields, and it has wide range of applications. In many of them, such as sensor databases, location-...
K-Nearest Neighbor Finding Using MaxNearestDist
Similarity searching often reduces to finding the k nearest neighbors to a query object. Finding the k nearest neighbors is achieved by applying either a depth- first or a best-first algorithm to the search hierarchy containing the data. These ...
Comments