By Jeff Erickson (auth.), Frank Dehne, Jörg-Rüdiger Sack, Norbert Zeh (eds.)
The papers during this quantity have been offered on the tenth Workshop on Algorithms and information constructions (WADS 2005). The workshop came about August 15 - 17, 2007, at Dalhousie college, Halifax, Canada. The workshop alternates with the Scandinavian Workshop on set of rules thought (SWAT), carrying on with the t- dition of SWAT and WADS beginning with SWAT 1988 and WADS 1989. From 142 submissions, this system Committee chosen fifty four papers for presentation on the workshop. additionally, invited lectures got through the next dist- guished researchers: Je? Erickson (University of Illinois at Urbana-Champaign) and Mike Langston (University of Tennessee). On behalf of this system Committee, we want to precise our honest appreciation to the numerous individuals whose e?ort contributed to creating WADS 2007 a hit. those contain the invited audio system, contributors of the guidance and ProgramCommittees, the authorswho submitted papers, andthe manyreferees who assisted this system Committee. we're indebted to Gerardo Reynaga for fitting and enhancing the submission software program, protecting the submission server and interacting with authors in addition to for assisting with the practise of the program.
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Additional info for Algorithms and Data Structures: 10th International Workshop, WADS 2007, Halifax, Canada, August 15-17, 2007. Proceedings
On Dynamic Range Reporting in One Dimension. In: Proc. 37th STOC 2005, pp. 104–111 (2005) 17. : Lower Bounds for 2-Dimensional Range Counting. In: Proc. 39th STOC 2007 (to appear) 18. : Tight Bounds for the Partial-Sums Problem. In: Proc. 15th SODA 2004, pp. 20–29 (2004) 19. : A Density Control Algorithm for Doing Insertions and Deletions in a Sequentially Ordered File in Good Worst-Case Time. jp Abstract. LSH (Locality Sensitive Hashing) is one of the best known methods for solving the c-approximate nearest neighbor problem in high dimensional spaces.
Theorem 3. There exists a data structure for two-dimensional orthogonal semigroup range sum queries that uses O(n log n/ log log n) space and supports queries in O((log n/ log log n)2 )) time and updates in O(log9/2+ε n) time. Proof. The data structure is organized in the same way as the data structures of Theorems 1 and 2, but in every node v of the range tree Tx a data structure Fv of Lemma 3 is stored. A two-dimensional range sum query can be answered by answering O(log n/ log log n) queries to data structures Fv .
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Algorithms and Data Structures: 10th International Workshop, WADS 2007, Halifax, Canada, August 15-17, 2007. Proceedings by Jeff Erickson (auth.), Frank Dehne, Jörg-Rüdiger Sack, Norbert Zeh (eds.)