Parameterized enumeration, transversals, and imperfect phylogeny reconstruction
Theoretical Computer Science - Parameterized and exact computation
Going Weighted: Parameterized Algorithms for Cluster Editing
COCOA 2008 Proceedings of the 2nd international conference on Combinatorial Optimization and Applications
ACM SIGACT News
TAMC '09 Proceedings of the 6th Annual Conference on Theory and Applications of Models of Computation
Going weighted: Parameterized algorithms for cluster editing
Theoretical Computer Science
Exact algorithms for cluster editing: evaluation and experiments
WEA'08 Proceedings of the 7th international conference on Experimental algorithms
Fixed-parameter algorithms for cluster vertex deletion
LATIN'08 Proceedings of the 8th Latin American conference on Theoretical informatics
A 2k Kernel for the cluster editing problem
COCOON'10 Proceedings of the 16th annual international conference on Computing and combinatorics
Algorithm engineering: bridging the gap between algorithm theory and practice
Algorithm engineering: bridging the gap between algorithm theory and practice
Generalized graph clustering: recognizing (p, q)-cluster graphs
WG'10 Proceedings of the 36th international conference on Graph-theoretic concepts in computer science
A novel branching strategy for parameterized graph modification problems
COCOA'10 Proceedings of the 4th international conference on Combinatorial optimization and applications - Volume Part II
Even faster parameterized cluster deletion and cluster editing
Information Processing Letters
Cograph editing: complexity and parameterized algorithms
COCOON'11 Proceedings of the 17th annual international conference on Computing and combinatorics
Improved Fixed-Parameter Algorithms for Minimum-Flip Consensus Trees
ACM Transactions on Algorithms (TALG)
A 2k kernel for the cluster editing problem
Journal of Computer and System Sciences
On making directed graphs transitive
Journal of Computer and System Sciences
Automated generation of simplification rules for SAT and MAXSAT
SAT'05 Proceedings of the 8th international conference on Theory and Applications of Satisfiability Testing
Fixed-parameter tractable generalizations of cluster editing
CIAC'06 Proceedings of the 6th Italian conference on Algorithms and Complexity
On the fixed-parameter enumerability of cluster editing
WG'05 Proceedings of the 31st international conference on Graph-Theoretic Concepts in Computer Science
Error compensation in leaf root problems
ISAAC'04 Proceedings of the 15th international conference on Algorithms and Computation
Applying modular decomposition to parameterized bicluster editing
IWPEC'06 Proceedings of the Second international conference on Parameterized and Exact Computation
Kernels: annotated, proper and induced
IWPEC'06 Proceedings of the Second international conference on Parameterized and Exact Computation
A golden ratio parameterized algorithm for cluster editing
IWOCA'11 Proceedings of the 22nd international conference on Combinatorial Algorithms
A golden ratio parameterized algorithm for Cluster Editing
Journal of Discrete Algorithms
Complexity and parameterized algorithms for Cograph Editing
Theoretical Computer Science
Efficient parameterized preprocessing for cluster editing
FCT'07 Proceedings of the 16th international conference on Fundamentals of Computation Theory
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We present a framework for an automated generation of exact search tree algorithms for NP-hard problems. The purpose of our approach is twofold—rapid development and improved upper bounds. Many search tree algorithms for various problems in the literature are based on complicated case distinctions. Our approach may lead to a much simpler process of developing and analyzing these algorithms. Moreover, using the sheer computing power of machines it may also lead to improved upper bounds on search tree sizes (i.e., faster exact solving algorithms) in comparison with previously developed “hand-made” search trees. Among others, such an example is given with the NP-complete Cluster Editing problem (also known as Correlation Clustering on complete unweighted graphs), which asks for the minimum number of edge additions and deletions to create a graph which is a disjoint union of cliques. The hand-made search tree for Cluster Editing had worst-case size O(2.27k), which now is improved to O(1.92k) due to our new method. (Herein, k denotes the number of edge modifications allowed.)