Kernelization, Partially Polynomial Kernels
- Christian KomusiewiczAffiliated withInstitut für Softwaretechnik und Theoretische Informatik Email author
KeywordsNP-hard problems Fixed-parameter algorithms Data reduction Kernelization
Years and Authors of Summarized Original Work
2011; Betzler, Guo, Komusiewicz, Niedermeier
2013; Basavaraju, Francis, Ramanujan, Saurabh
2014; Betzler, Bredereck, Niedermeier
In parameterized complexity, each instance (I, k) of a problem comes with an additional parameter k which describes structural properties of the instance, for example, the maximum degree of an input graph. A problem is called fixed-parameter tractable if it can be solved in f(k) ⋅poly(n) time, that is, the super-polynomial part of the running time depends only on k. Consequently, instances of the problem can be solved efficiently if k is small.
One way to show fixed-parameter tractability of a problem is the design of a polynomial-time data reduction algorithm that reduces any input instance (I, k) to one whose size is bounded in k. This idea is captured by the notion of kernelization.
Let (I, k) be an instance of a parameterized problem P, where I ∈ Σ ∗ denotes the input instance and ...
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Date: 2014 (Latest)History
- 2014 (Latest)
- Kernelization, Partially Polynomial Kernels
- Reference Work Title
- Encyclopedia of Algorithms
- pp 1-4
- Online ISBN
- Springer US
- Copyright Holder
- Springer Science+Business Media New York
- NP-hard problems
- Fixed-parameter algorithms
- Data reduction
- Industry Sectors
- eBook Packages
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