Geometric optimization problems over sliding windows

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3341, Issue , 2004, Pages 246-258

  Chan, Timothy M ^a   Sadjad, Bashir S ^a  

^a UNIVERSITY OF WATERLOO   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

COMMUNICATION CHANNELS (INFORMATION THEORY); DECODING; OPTIMIZATION; APPROXIMATION ALGORITHMS; GEOMETRY;

CONSTANT-FACTOR APPROXIMATION ALGORITHMS; GEOMETRIC OPTIMIZATION; ONE DIMENSION; ONE-DIMENSIONAL; OPTIMIZATION PROBLEMS; POINT SET; SIMPLE ALGORITHM; SIMPLER ALGORITHMS; SLIDING WINDOW; SLIDING WINDOW MODELS; SUBLINEAR;

APPROXIMATION ALGORITHMS; OPTIMIZATION;

EID: 35048848038     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-30551-4_23     Document Type: Article

References (17)

1. P. K. Agarwal, S. Har-Peled, and R. Varadarajan. Approximating extent measures of points. Journal of the ACM, to appear.
2. P. K. Agarwal, J. Matoušek, and S. Suri. Farthest neighbors, maximum spanning trees and related problems in higher dimensions. Computational Geometry: Theory and Applications, 1:189-201, 1991.
3. P. K. Agarwal and M. Sharir. Efficient randomized algorithms for some geometric optimization problems. Discrete & Computational Geometry, 16:317-337, 1996.
4. G. Barequet and S. Har-Peled. Efficiently approximating the minimum-volume bounding box of a point set in three dimensions. Journal of Algorithms, 38:91-109, 2001.
5. J. L. Bentley and J. B. Saxe. Decomposable searching problems I: Static-to-dynamic transformations. Journal of Algorithms, 1(4):301-358, 1980.
6. T. M. Chan. Approximating the diameter, width, smallest enclosing cylinder, and minimum-width annulus. International Journal on Computational Geometry and Applications, 12:67-85, 2002.
7. T. M. Chan. Faster core-set constructions and data stream algorithms in fixed dimensions. In Proceedings of the 20th Annual Symposium on Computational Geometry, pages 152-159, 2004.
8. K. L. Clarkson and P. W. Shor. Applications of random sampling in computational geometry, II. Discrete & Computational Geometry, 4(1):387-421, 1989.
9. C. A. Duncan, M. T. Goodrich, and E. A. Ramos. Efficient approximation and optimization algorithms for computational metrology. In Proceedings of the Eighth Annual ACM-SIAM Symposium on Discrete Algorithms, pages 121-130, 1997.
10. J. Feigenbaum, S. Kannan, and J. Zhang. Computing diameter in the streaming and sliding-window models. Algorithmica, to appear; or as Tech. Report DCS/TR-1245, Yale University, http://cs-www.cs.yale.edu/homes/jf/FKZ.ps, 2002.
11. A. Goel, P. Indyk, and K. Varadarajan. Reductions among high dimensional proximity problems. In Proceedings of the Twelfth Annual ACM-SIAM Symposium on Discrete Algorithms, pages 769-778, 2001.
12. M. Henzinger, P. Raghavan, and S. Rajagopalan. Computing on data streams. Technical Report SRC-TN-1998-011, Hewlett Packard Laboratories, 1998.
13. J. Hershberger and S. Suri. Convex hulls and related problems in data streams. In ACM SIGMOD/PODS Workshop on Management and Processing of Data Streams, pages 148-168, 2003.
14. P. Indyk. Better algorithms for high-dimensional proximity problems via asymmetric embeddings. In Proceedings of the Fourteenth Annual ACM-SIAM Symposium on Discrete Algorithms, pages 539-545, 2003.
15. S.M.Muthukrishnan. Datastreams: Algorithms and applications. Rutgers University Technical Report, http://athos.rutgers.edu/~muthu/stream-1-1.ps, 2003.
16. F. P. Preparata and M. I. Shamos. Computational Geometry: An Introduction. Springer-Verlag, 1985.
17. E. A. Ramos. An optimal deterministic algorithm for computing the diameter of a three-dimensional point set. Discrete & Computational Geometry, 26:233-244, 2001.