Leonid A. Levin: Difference between revisions
Created page with "Title: Leonid A. Levin Main Research Question: How can the distortive effects of corporate, dividend, and capital gains taxes be eliminated while maintaining tax revenue? Methodology: The study proposes a new tax system called the Equity Tax. This system is designed to work exclusively for publicly held corporations. The main idea is to use the share prices to reflect the expected true annual return, as perceived by investors, not as defined by law. The system works b..." |
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Title: Leonid A. Levin | Title: Leonid A. Levin | ||
Research Question: Can random instances of a graph coloring problem be hard on average? | |||
Methodology: The | Methodology: The researchers used a random graph problem and introduced randomizing reductions to show the intractability of random instances of a graph coloring problem. | ||
Results: The | Results: The researchers proved that the graph problem is hard on average unless all NP problems under all samplable distributions are easy. This poses significant technical difficulties. | ||
Implications: | Implications: This work provides a strong hardness result related to "typical" or "average" instances of a problem, which is crucial for understanding the efficiency of algorithms and the P=NP question. It also shows that average case completeness of a random graph problem is unlikely without introducing randomizing reductions. | ||
Link to Article: https://arxiv.org/abs/ | Link to Article: https://arxiv.org/abs/0112001v9 | ||
Authors: | Authors: | ||
arXiv ID: | arXiv ID: 0112001v9 | ||
[[Category:Computer Science]] | [[Category:Computer Science]] | ||
[[Category:Problem]] | |||
[[Category:Graph]] | |||
[[Category:Random]] | |||
[[Category:Average]] | |||
[[Category:Instances]] |
Latest revision as of 03:43, 24 December 2023
Title: Leonid A. Levin
Research Question: Can random instances of a graph coloring problem be hard on average?
Methodology: The researchers used a random graph problem and introduced randomizing reductions to show the intractability of random instances of a graph coloring problem.
Results: The researchers proved that the graph problem is hard on average unless all NP problems under all samplable distributions are easy. This poses significant technical difficulties.
Implications: This work provides a strong hardness result related to "typical" or "average" instances of a problem, which is crucial for understanding the efficiency of algorithms and the P=NP question. It also shows that average case completeness of a random graph problem is unlikely without introducing randomizing reductions.
Link to Article: https://arxiv.org/abs/0112001v9 Authors: arXiv ID: 0112001v9