By Mikkel Thorup, David R. Karger (auth.)

ISBN-10: 354044985X

ISBN-13: 9783540449850

ISBN-10: 3540676902

ISBN-13: 9783540676904

This ebook constitutes the refereed complaints of the seventh Scandinavian Workshop on set of rules idea, SWAT 2000, held in Bergen, Norway, in July 2000.

The forty three revised complete papers provided including three invited contributions have been rigorously reviewed and chosen from a complete of a hundred and five submissions. The papers are geared up in sections on facts constructions, dynamic walls, graph algorithms, on-line algorithms, approximation algorithms, matchings, community layout, computational geometry, strings and set of rules engineering, exterior reminiscence algorithms, optimization, and allotted and fault-tolerant computing.

**Read Online or Download Algorithm Theory - SWAT 2000: 7th Scandinavian Workshop on Algorithm Theory Bergen, Norway, July 5–7, 2000 Proceedings PDF**

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**Additional info for Algorithm Theory - SWAT 2000: 7th Scandinavian Workshop on Algorithm Theory Bergen, Norway, July 5–7, 2000 Proceedings**

**Example text**

We need the following slight extension of his result to also solve the second problem: Lemma 3. (Hagerup) Given a set T of m elements, divided into equivalence classes, a discriminating bit position i can be found in time O(m) by a deterministic, weakly non-uniform algorithm. Further, for any set I ⊆ {0, . . , 4w −1} of size O((log n)4 ) (given as a bit vector), we can assure that i ∈ I. Proof sketch. It can be shown how to compute |{{x, y} ⊆ T | x = y, x ≡ y, e(x)i = e(y)i }| for all i ∈ {0, .

Without update operations) can have constant query time and linear space consumption. Allowing randomization, the FKS static dictionary can be made dynamic, supporting insertions and deletions in amortized expected constant time [4]. e. probability at least 1 − n−c , where c is any constant of our choice). A simpler dictionary with the same properties was later developed [3]. As for randomized dictionaries, this leaves very little to be improved. Without a source of random bits, the task of simultaneously achieving fast updates and constant query time seems considerably harder.

Brown, Exploring the metabolic and genetic control of gene expression on a genomic scale, Science 278 (1997) 680–686. 5. D. Gusfield, Algorithms on Strings, Trees, and Sequences – Computer Science and Computational Biology, Cambridge University Press 1997. 6. uk/∼vilo/Expression Profiler/ 7. H. Peltola, H. S¨ oderlund, J. Tarhio & E. Ukkonen, Algorithms for some string matching problems arising in molecular genetics, Proc. 9th IFIP World Computer Congress, Elsevier (1983) 59–64. 8. R. Staden, Automation of the computer handling of gel reading data produced by the shotgun method of DNA sequencing, Nucleic Acids Research 10 (1982), 4731–4751.

### Algorithm Theory - SWAT 2000: 7th Scandinavian Workshop on Algorithm Theory Bergen, Norway, July 5–7, 2000 Proceedings by Mikkel Thorup, David R. Karger (auth.)

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