Titlebook: Algorithms and Computation; 18th International S Takeshi Tokuyama Conference proceedings 2007 Springer-Verlag Berlin Heidelberg 2007 Algori

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Unbounded-Error Classical and Quantum Communication Complexityen studied based on the arrangement of points and hyperplanes. Recently, [14, ICALP’07] found that the unbounded-error . communication complexity in the . model can also be investigated using the arrangement, and showed that it is exactly (without a difference of even one qubit) half of the classica

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A Spectral Method for MAX2SAT in the Planted Solution Modelposed a distribution . for MAX2SAT in the planted solution model, as well as a message-passing algorithm. They showed that it solves, ., MAX2SAT on . for rather dense formulas, i.e., the expected number of clauses is .. In this paper, we propose an algorithm using a spectral method and a variant of

遠(yuǎn)地點(diǎn)

On the Expressive Power of Planar Perfect Matching and Permanents of Bounded Treewidth Matricesof the classical classes P and NP. Prominent examples of difficult (that is, VNP-complete) problems in this model includes the permanent and hamiltonian polynomials. In this paper we investigate the expressive power of easy special cases of these polynomials. We show that the permanent and hamiltoni

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幸福愉悅感

Computing Upward Topological Book Embeddings of Upward Planar Digraphs where all edges are monotonically increasing in the upward direction. Besides having its own inherent interest in the theory of upward book embeddability, the question has applications to well studied research topics of computational geometry and of graph drawing. The main results of the paper are

金哥占卜者

Algorithms for the Hypergraph and the Minor Crossing Number Problemsed before. We present some complexity results regarding the corresponding edge and node insertion problems. Based on these results, we give the first embedding-based heuristics to tackle both problems and present a short experimental study. Furthermore, we give the first exact ILP formulation for bo

鋼盔

On Mixing and Edge Expansion Properties in Randomized BroadcastingInitially, only one vertex of a graph .?=?(.,.) owns a piece of information which is spread iteratively to all other vertices: in each time step .?=?1,2,... every . vertex chooses some neighbor uniformly at random which then becomes informed and may itself inform other vertices in the succeeding tim

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Algorithms and Computation978-3-540-77120-3Series ISSN 0302-9743 Series E-ISSN 1611-3349