1,588 research outputs found

    Hybrid VCSPs with crisp and conservative valued templates

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    A constraint satisfaction problem (CSP) is a problem of computing a homomorphism R→Γ{\bf R} \rightarrow {\bf \Gamma} between two relational structures. Analyzing its complexity has been a very fruitful research direction, especially for fixed template CSPs, denoted CSP(Γ)CSP({\bf \Gamma}), in which the right side structure Γ{\bf \Gamma} is fixed and the left side structure R{\bf R} is unconstrained. Recently, the hybrid setting, written CSPH(Γ)CSP_{\mathcal{H}}({\bf \Gamma}), where both sides are restricted simultaneously, attracted some attention. It assumes that R{\bf R} is taken from a class of relational structures H\mathcal{H} that additionally is closed under inverse homomorphisms. The last property allows to exploit algebraic tools that have been developed for fixed template CSPs. The key concept that connects hybrid CSPs with fixed-template CSPs is the so called "lifted language". Namely, this is a constraint language ΓR{\bf \Gamma}_{{\bf R}} that can be constructed from an input R{\bf R}. The tractability of that language for any input R∈H{\bf R}\in\mathcal{H} is a necessary condition for the tractability of the hybrid problem. In the first part we investigate templates Γ{\bf \Gamma} for which the latter condition is not only necessary, but also is sufficient. We call such templates Γ{\bf \Gamma} widely tractable. For this purpose, we construct from Γ{\bf \Gamma} a new finite relational structure Γ′{\bf \Gamma}' and define H0\mathcal{H}_0 as a class of structures homomorphic to Γ′{\bf \Gamma}'. We prove that wide tractability is equivalent to the tractability of CSPH0(Γ)CSP_{\mathcal{H}_0}({\bf \Gamma}). Our proof is based on the key observation that R{\bf R} is homomorphic to Γ′{\bf \Gamma}' if and only if the core of ΓR{\bf \Gamma}_{{\bf R}} is preserved by a Siggers polymorphism. Analogous result is shown for valued conservative CSPs.Comment: 21 pages. arXiv admin note: text overlap with arXiv:1504.0706

    The power of Sherali-Adams relaxations for general-valued CSPs

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    We give a precise algebraic characterisation of the power of Sherali-Adams relaxations for solvability of valued constraint satisfaction problems to optimality. The condition is that of bounded width which has already been shown to capture the power of local consistency methods for decision CSPs and the power of semidefinite programming for robust approximation of CSPs. Our characterisation has several algorithmic and complexity consequences. On the algorithmic side, we show that several novel and many known valued constraint languages are tractable via the third level of the Sherali-Adams relaxation. For the known languages, this is a significantly simpler algorithm than the previously obtained ones. On the complexity side, we obtain a dichotomy theorem for valued constraint languages that can express an injective unary function. This implies a simple proof of the dichotomy theorem for conservative valued constraint languages established by Kolmogorov and Zivny [JACM'13], and also a dichotomy theorem for the exact solvability of Minimum-Solution problems. These are generalisations of Minimum-Ones problems to arbitrary finite domains. Our result improves on several previous classifications by Khanna et al. [SICOMP'00], Jonsson et al. [SICOMP'08], and Uppman [ICALP'13].Comment: Full version of an ICALP'15 paper (arXiv:1502.05301

    Normalized Web Distance and Word Similarity

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    There is a great deal of work in cognitive psychology, linguistics, and computer science, about using word (or phrase) frequencies in context in text corpora to develop measures for word similarity or word association, going back to at least the 1960s. The goal of this chapter is to introduce the normalizedis a general way to tap the amorphous low-grade knowledge available for free on the Internet, typed in by local users aiming at personal gratification of diverse objectives, and yet globally achieving what is effectively the largest semantic electronic database in the world. Moreover, this database is available for all by using any search engine that can return aggregate page-count estimates for a large range of search-queries. In the paper introducing the NWD it was called `normalized Google distance (NGD),' but since Google doesn't allow computer searches anymore, we opt for the more neutral and descriptive NWD. web distance (NWD) method to determine similarity between words and phrases. ItComment: Latex, 20 pages, 7 figures, to appear in: Handbook of Natural Language Processing, Second Edition, Nitin Indurkhya and Fred J. Damerau Eds., CRC Press, Taylor and Francis Group, Boca Raton, FL, 2010, ISBN 978-142008592
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