This paper combines Qdags with a Generalized Hypertree Decomposition of the query, into subqueries with fewer variables, and implements algorithms that find the optimal GHD according to the AGM bounds of the subqueries and the specificities of the Qdag cost model.
This paper presents the first in-depth discussion of rerootability in hypertree decompositions, and defines a relaxed notion of normal form which leads to a truly rerootable and tractable class.
Zhe-Kai Jiang, Christoph Koch, Peter Lindner et al.· 0 citations
This paper provides a tight reduction demonstrating that any exact distance sensitivity oracle can be used to efficiently solve decremental exact diameter and all-node eccentricities and introduces two new instructive techniques and demonstrates how to utilize them to construct several new algorithms.
Sam Hiken, Yael Kirkpatrick, Jakob Nogler et al.· 0 citations
In this paper, the parameterized complexity of the multiplicative $\alpha$-spanner problem with independent weights and lengths on undirected graphs is considered for the first time. All prior FPT results (except one on DAGs) assume basic instances (i.e., with unit weights and lengths) and are parameterized in the stre...
Marius Bächler, Markus Chimani, Henning Jasper· 0 citations
Recent work by Haeupler, Hlad\'ik, Rozhon, Tarjan, and T\v{e}tek on the instance optimality of shortest-path algorithms established several results concerning Dijkstra's algorithm and bidirectional Dijkstra's algorithm in weighted and unweighted graphs. Motivated by these results, we revisit the question of instance op...
The Graph Coloring Problem (GCP) is NP-hard and DSATUR stands as one of the fastest heuristics for it despite producing colorings that typically use more colors than state-of-the-art coloring algorithms. We propose SSLD (Semidefinite Spectral Learning with DSATUR), which improves DSATUR by preprocessing a first good co...
Density decomposition characterizes the multi-level dense structure of large networks and supports a wide range of graph mining applications. Given a graph
G = (V, E)
, it assigns each vertex an integral dense number (IDN) and produces a nested sequence of layers D
0
⊇ D
1
⊇ ... ⊇ D
p
that capture increasingl...
Ya-Long Zhang, Rong-Hua Li, Qi Zhang et al.· Proceedings of the ACM on Ma...· 0 citations
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