Derandomization through approximation: an NC algorithm for minimum cuts
Abstract: "We prove that the minimum cut problem can be solved in NC on arbitrarily weighted undirected graphs. We do so by giving three separate and independently interesting results. The first is a relatively straightforward NC (2 + [epsilon])-approximation algorithm for the minimum cut. It u...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Stanford, Calif.
1993
|
| Series: | Stanford University / Computer Science Department: Report STAN CS
1471 |
| Subjects: | |
| Summary: | Abstract: "We prove that the minimum cut problem can be solved in NC on arbitrarily weighted undirected graphs. We do so by giving three separate and independently interesting results. The first is a relatively straightforward NC (2 + [epsilon])-approximation algorithm for the minimum cut. It uses O(m²/n) processors. The second result is a randomized reduction of the minimum cut problem to the minimum cut approximation problem. The third is a derandomization of this reduction. Performing the derandomization requires a novel combination of two previously known derandomization techniques: pairwise independence and random walks on expanders." |
| Physical Description: | 18 S. |
Staff View
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| 520 | 3 | |a Abstract: "We prove that the minimum cut problem can be solved in NC on arbitrarily weighted undirected graphs. We do so by giving three separate and independently interesting results. The first is a relatively straightforward NC (2 + [epsilon])-approximation algorithm for the minimum cut. It uses O(m²/n) processors. The second result is a randomized reduction of the minimum cut problem to the minimum cut approximation problem. The third is a derandomization of this reduction. Performing the derandomization requires a novel combination of two previously known derandomization techniques: pairwise independence and random walks on expanders." | |
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Record in the Search Index
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| indexdate | 2024-07-09T17:28:58Z |
| institution | BVB |
| language | English |
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| series2 | Stanford University / Computer Science Department: Report STAN CS |
| spelling | Karger, David Verfasser aut Derandomization through approximation an NC algorithm for minimum cuts by David Karger and Rajeev Motwani Stanford, Calif. 1993 18 S. txt rdacontent n rdamedia nc rdacarrier Stanford University / Computer Science Department: Report STAN CS 1471 Abstract: "We prove that the minimum cut problem can be solved in NC on arbitrarily weighted undirected graphs. We do so by giving three separate and independently interesting results. The first is a relatively straightforward NC (2 + [epsilon])-approximation algorithm for the minimum cut. It uses O(m²/n) processors. The second result is a randomized reduction of the minimum cut problem to the minimum cut approximation problem. The third is a derandomization of this reduction. Performing the derandomization requires a novel combination of two previously known derandomization techniques: pairwise independence and random walks on expanders." Random walks (Mathematics) Motwani, Rajeev 1962-2009 Verfasser (DE-588)124195199 aut Computer Science Department: Report STAN CS Stanford University 1471 (DE-604)BV008928280 1471 |
| spellingShingle | Karger, David Motwani, Rajeev 1962-2009 Derandomization through approximation an NC algorithm for minimum cuts Random walks (Mathematics) |
| title | Derandomization through approximation an NC algorithm for minimum cuts |
| title_auth | Derandomization through approximation an NC algorithm for minimum cuts |
| title_exact_search | Derandomization through approximation an NC algorithm for minimum cuts |
| title_full | Derandomization through approximation an NC algorithm for minimum cuts by David Karger and Rajeev Motwani |
| title_fullStr | Derandomization through approximation an NC algorithm for minimum cuts by David Karger and Rajeev Motwani |
| title_full_unstemmed | Derandomization through approximation an NC algorithm for minimum cuts by David Karger and Rajeev Motwani |
| title_short | Derandomization through approximation |
| title_sort | derandomization through approximation an nc algorithm for minimum cuts |
| title_sub | an NC algorithm for minimum cuts |
| topic | Random walks (Mathematics) |
| topic_facet | Random walks (Mathematics) |
| volume_link | (DE-604)BV008928280 |
| work_keys_str_mv | AT kargerdavid derandomizationthroughapproximationanncalgorithmforminimumcuts AT motwanirajeev derandomizationthroughapproximationanncalgorithmforminimumcuts |