K. Mehlhorn

Publications561
h-index70
Citations19,154
Highly Influential Citations1,167
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Weisfeiler-Lehman Graph Kernels
TLDR
A family of efficient kernels for large graphs with discrete node labels based on the Weisfeiler-Lehman test of isomorphism on graphs that outperform state-of-the-art graph kernels on several graph classification benchmark data sets in terms of accuracy and runtime.
LEDA: a platform for combinatorial and geometric computing
TLDR
There is no standard library of the data structures and algorithms of combinatorial and geometric computing, and there are, for example, packages in statistics (SPSS), numerical analysis (LINPACK), symbolic computation (MAPLE, MATHEMATICA), and linear programming (CPLEX).
Efficient graphlet kernels for large graph comparison
TLDR
In this article, two theoretically grounded speedup schemes are introduced, one based on sampling and the second specifically designed for bounded degree graphs, to efficiently compare large graphs that cannot be tackled by existing graph kernels.
Faster algorithms for the shortest path problem
Efficient implementations of Dijkstra's shortest path algorithm are investigated. A new data structure, called the <italic>radix heap</italic>, is proposed for use in this algorithm. On a network…
The LEDA Platform of Combinatorial and Geometric Computing
TLDR
An overview of the LEDA platform for combinatorial and geometric computing and an account of its development are given and some recent theoretical developments are discussed.
A Faster Approximation Algorithm for the Steiner Problem in Graphs
  • K. Mehlhorn
  • Mathematics
    Inf. Process. Lett.
  • 25 March 1988
A Parallelization of Dijkstra's Shortest Path Algorithm
TLDR
A PRAM algorithm is given based on Dijkstra's sequential SSSP algorithm into a number of phases, such that the operations within a phase can be done in parallel.
Data Structures and Algorithms 1: Sorting and Searching
  • K. Mehlhorn
  • Computer Science
    EATCS Monographs on Theoretical Computer Science
  • 8 December 2011
Popular matchings
TLDR
The first polynomial-time algorithms to determine if an instance admits a popular matching, and to find a largest such matching, if one exists are given.
Dynamic perfect hashing: upper and lower bounds
TLDR
An Omega (log n) lower bound is proved for the amortized worst-case time complexity of any deterministic algorithm in a class of algorithms encompassing realistic hashing-based schemes.
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