A fast algorithm for the maximum clique problem
Discrete Applied Mathematics - Sixth Twente Workshop on Graphs and Combinatorial Optimization
Crown Structures for Vertex Cover Kernelization
Theory of Computing Systems
Fast fixed-parameter tractable algorithms for nontrivial generalizations of vertex cover
Discrete Applied Mathematics
A parallel algorithm for enumerating all the maximal k-plexes
PAKDD'07 Proceedings of the 2007 international conference on Emerging technologies in knowledge discovery and data mining
Isolation concepts for enumerating dense subgraphs
COCOON'07 Proceedings of the 13th annual international conference on Computing and Combinatorics
A Complexity Dichotomy for Finding Disjoint Solutions of Vertex Deletion Problems
ACM Transactions on Computation Theory (TOCT)
On making a distinguished vertex minimum degree by vertex deletion
SOFSEM'11 Proceedings of the 37th international conference on Current trends in theory and practice of computer science
On social-temporal group query with acquaintance constraint
Proceedings of the VLDB Endowment
A generalization of Nemhauser and Trotter's local optimization theorem
Journal of Computer and System Sciences
A More Relaxed Model for Graph-Based Data Clustering: $s$-Plex Cluster Editing
SIAM Journal on Discrete Mathematics
Modeling affiliations in networks
Proceedings of the Winter Simulation Conference
| Hi-index | 0.00 |
We propose new practical algorithms to find degree-relaxed variants of cliques called s -plexes. An s -plex denotes a vertex subset in a graph inducing a subgraph where every vertex has edges to all but at most s vertices in the s -plex. Cliques are 1-plexes. In analogy to the special case of finding maximum-cardinality cliques, finding maximum-cardinality s -plexes is NP-hard. Complementing previous work, we develop combinatorial, exact algorithms, which are strongly based on methods from parameterized algorithmics. The experiments with our freely available implementation indicate the competitiveness of our approach, for many real-world graphs outperforming the previously used methods.