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New Frontiers in Parameterized Complexity and Algorithms
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The research on parameterized complexity (PC), described in these peer-reviewed chapters by esteemed researchers, provides ties to practice as well as new theoretical developments, many in the direction of AI. Applications in bioinformatics and social choice are described, as well as faster, less costly approximation methods and new techniques using machine learning to find treewidth and other metrics. Many practical problems can be solved by harnessing the power of both PC and SAT solvers or integer linear programming modeled by parameterized graph problems. The extremely rapid development and deployment of PC continues to bring fresh understanding and solutions to fundamental open questions.
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Keywords
- agreement forests
- algorithm selection
- Approximation Algorithms
- bounded search tree
- cascade failure
- combinatorial optimisation
- Comparative genomics
- dominating set
- Enumeration
- ETH/SETH
- expected coverage
- feedback vertex set
- fine-grained
- fixed-parameter tractability
- FPT
- fpt-reductions
- genome assembly
- Hamming distance
- haplotyping
- hardness of approximation
- heuristics
- hitting sets
- inapproximability
- influence maximization
- integer linear programming
- kernelization
- kidney exchange problem
- linear reliable ordering
- lower bounds
- Machine learning
- Model Checking
- multilinear monomial detection
- ordering
- parameterised complexity
- parameterised enumeration
- parameterized AC0
- parameterized algorithm
- parameterized complexity
- phylogenetics
- polynomial hierarchy
- probabilistic core.
- probabilistic graphs
- random partitioning
- randomized algorithm
- sequence analysis
- solution diversity
- thema EDItEUR::U Computing and Information Technology
- thema EDItEUR::U Computing and Information Technology::UY Computer science
- tree decomposition
- treedepth
- treewidth
- turbo-charged
- uncertain graphs
- vertex cover
Links
DOI: 10.3390/books978-3-7258-1302-5Editions