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REPORTS > AUTHORS > URI ZWICK:
All reports by Author Uri Zwick:

TR00-060 | 17th August 2000
Uri Zwick

All Pairs Shortest Paths using Bridging Sets and Rectangular Matrix Multiplication

We present two new algorithms for solving the {\em All Pairs Shortest Paths\/} (APSP) problem for weighted directed graphs. Both algorithms use fast matrix multiplication algorithms. The first algorithm solves the APSP problem for weighted directed graphs in which the edge weights are integers of small absolute value in $\Ot(n^{2+\mu})$ ... more >>>

TR97-040 | 17th September 1997
Dorit Dor, Shay Halperin, Uri Zwick

All Pairs Almost Shortest Paths

Let G=(V,E) be an unweighted undirected graph on n vertices. A simple argument shows that computing all distances in G with an additive one-sided error of at most 1 is as hard as Boolean matrix multiplication. Building on recent work of Aingworth, Chekuri and Motwani, we describe an \tilde{O}(min{n^{3/2}m^{1/2},n^{7/3}) time ... more >>>

TR95-040 | 26th July 1995
Uri Zwick, Michael S. Paterson

The complexity of mean payoff games on graphs

We study the complexity of finding the values and optimal strategies of MEAN PAYOFF GAMES on graphs, a family of perfect information games introduced by Ehrenfeucht and Mycielski and considered by Gurvich, Karzanov and Khachiyan. We describe a pseudo-polynomial time algorithm for the solution of such games, the decision problem ... more >>>

TR95-031 | 25th June 1995
Dorit Dor, Uri Zwick

Selecting the median

Improving a long standing result of Sch\"{o}nhage, Paterson and Pippenger we show that the MEDIAN of a set containing n elements can always be found using at most 2.95n comparisons. This is the full version of the paper. An extended abstract version of the paper apperead in the proceedings SODA'95. more >>>

TR94-009 | 12th December 1994
Noga Alon, Raphael Yuster, Uri Zwick

Color-coding

We describe a novel randomized method, the method of {\em color-coding\/} for finding simple paths and cycles of a specified length $k$, and other small subgraphs, within a given graph $G=(V,E)$. The randomized algorithms obtained using this method can be derandomized using families of {\em perfect hash functions\/}. Using the ... more >>>



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