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Decomposition

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Marc Gyssens – One of the best experts on this subject based on the ideXlab platform.

  • a unified theory of structural tractability for constraint satisfaction problems
    Journal of Computer and System Sciences, 2008
    Co-Authors: David Cohen, Peter Jeavons, Marc Gyssens
    Abstract:

    In this paper we derive a generic form of structural Decomposition for the constraint satisfaction problem, which we call a guarded Decomposition. We show that many existing Decomposition methods can be characterised in terms of finding guarded Decompositions satisfying certain specified additional conditions. Using the guarded Decomposition framework we are also able to define a new form of Decomposition, which we call a spread-cut. We show that the discovery of width-k spread-cut Decompositions is tractable for each k, and that spread-cut Decompositions strongly generalise many existing Decomposition methods. Finally we exhibit a family of hypergraphs H”n, for n=1,2,3…, where the minimum width of any hypertree Decomposition of each H”n is 3n, but the width of the best spread-cut Decomposition is only 2n+1.

  • a unified theory of structural tractability for constraint satisfaction and spread cut Decomposition
    International Joint Conference on Artificial Intelligence, 2005
    Co-Authors: David Cohen, Peter Jeavons, Marc Gyssens
    Abstract:

    In this paper we introduce a generic form of structural Decomposition for the constraint satisfaction problem, which we call a guarded Decomposition. We show that many existing Decomposition methods can be characterized in terms of finding guarded Decompositions satisfying certain specified additional conditions. Using the guarded Decomposition framework we are also able to define a new form of Decomposition, which we call a spread cut. We show that discovery of width k spread-cut Decompositions is tractable for each k, and that the spread cut Decomposition strongly generalize all existing Decompositions except hypertrees. Finally we exhibit a family of hypergraphs Hn, for n = 1, 2, 3 …, where the width of the best hypertree Decomposition of each Hn is at least 3n, but the width of the best spreadcut Decomposition is at most 2n.

Dan Segal – One of the best experts on this subject based on the ideXlab platform.

  • a variance Decomposition primer for accounting research
    Journal of Accounting Auditing & Finance, 2010
    Co-Authors: Jeffrey L Callen, Dan Segal
    Abstract:

    This pedagogical note introduces the accounting-based variance Decomposition methodology of Vuolteenaho (2002) in a relatively simple format for the edification of accounting scholars and doctoral students who wish to use variance Decomposition in their research. In addition to presenting an example that explicates the variance Decomposition approach, we provide well-documented SAS and STATA programs for estimating variance Decompositions from cross-sectional time-series data.

Shigeo Matsubara – One of the best experts on this subject based on the ideXlab platform.

  • efficient task Decomposition in crowdsourcing
    Pacific Rim International Conference on Multi-Agents, 2014
    Co-Authors: Huan Jiang, Shigeo Matsubara
    Abstract:

    In order to facilitate crowdsourcing-based task solving, complex tasks are decomposed into smaller subtasks that can be executed either sequentially or in parallel by workers. These two task Decompositions attract a plenty of empirical explorations in crowdsourcing. However the absence of formal study makes difficulty in providing task requesters with explicit guidelines on task Decomposition. In this paper, we formally present and analyze those two task Decompositions as vertical and horizontal task Decomposition models. Our focus is on addressing the efficiency (i.e., the quality of the task’s solution) of task Decomposition when the self-interested workers are paid in two different ways — equally paid and paid based on their contributions. By combining the theoretical analyses on worker’s behavior and simulation-based exploration on the efficiency of task Decomposition, our study 1) shows the superiority of vertical task Decomposition over horizontal task Decomposition in improving the quality of the task’s solution; 2) gives explicit instructions on strategies for optimal vertical task Decomposition under both revenue sharing schemes to maximize the quality of the task’s solution.

  • PRIMA – Efficient Task Decomposition in Crowdsourcing
    PRIMA 2014: Principles and Practice of Multi-Agent Systems, 2014
    Co-Authors: Huan Jiang, Shigeo Matsubara
    Abstract:

    In order to facilitate crowdsourcing-based task solving, complex tasks are decomposed into smaller subtasks that can be executed either sequentially or in parallel by workers. These two task Decompositions attract a plenty of empirical explorations in crowdsourcing. However the absence of formal study makes difficulty in providing task requesters with explicit guidelines on task Decomposition. In this paper, we formally present and analyze those two task Decompositions as vertical and horizontal task Decomposition models. Our focus is on addressing the efficiency (i.e., the quality of the task’s solution) of task Decomposition when the self-interested workers are paid in two different ways — equally paid and paid based on their contributions. By combining the theoretical analyses on worker’s behavior and simulation-based exploration on the efficiency of task Decomposition, our study 1) shows the superiority of vertical task Decomposition over horizontal task Decomposition in improving the quality of the task’s solution; 2) gives explicit instructions on strategies for optimal vertical task Decomposition under both revenue sharing schemes to maximize the quality of the task’s solution.

David Cohen – One of the best experts on this subject based on the ideXlab platform.

  • a unified theory of structural tractability for constraint satisfaction problems
    Journal of Computer and System Sciences, 2008
    Co-Authors: David Cohen, Peter Jeavons, Marc Gyssens
    Abstract:

    In this paper we derive a generic form of structural Decomposition for the constraint satisfaction problem, which we call a guarded Decomposition. We show that many existing Decomposition methods can be characterised in terms of finding guarded Decompositions satisfying certain specified additional conditions. Using the guarded Decomposition framework we are also able to define a new form of Decomposition, which we call a spread-cut. We show that the discovery of width-k spread-cut Decompositions is tractable for each k, and that spread-cut Decompositions strongly generalise many existing Decomposition methods. Finally we exhibit a family of hypergraphs H”n, for n=1,2,3…, where the minimum width of any hypertree Decomposition of each H”n is 3n, but the width of the best spread-cut Decomposition is only 2n+1.

  • a unified theory of structural tractability for constraint satisfaction and spread cut Decomposition
    International Joint Conference on Artificial Intelligence, 2005
    Co-Authors: David Cohen, Peter Jeavons, Marc Gyssens
    Abstract:

    In this paper we introduce a generic form of structural Decomposition for the constraint satisfaction problem, which we call a guarded Decomposition. We show that many existing Decomposition methods can be characterized in terms of finding guarded Decompositions satisfying certain specified additional conditions. Using the guarded Decomposition framework we are also able to define a new form of Decomposition, which we call a spread cut. We show that discovery of width k spread-cut Decompositions is tractable for each k, and that the spread cut Decomposition strongly generalize all existing Decompositions except hypertrees. Finally we exhibit a family of hypergraphs Hn, for n = 1, 2, 3 …, where the width of the best hypertree Decomposition of each Hn is at least 3n, but the width of the best spreadcut Decomposition is at most 2n.

H.j. Whitehouse – One of the best experts on this subject based on the ideXlab platform.

  • ISSPA – A joint time-frequency empirical mode Decomposition for nonstationary signal separation
    2007 9th International Symposium on Signal Processing and Its Applications, 2020
    Co-Authors: Nathan J. Stevenson, B. Boashash, Mahmoud Mesbah, H.j. Whitehouse
    Abstract:

    This paper outlines the application of the empirical mode Decomposition (EMD) to a frequency domain representation of a signal. The application to frequency domain representations, as opposed to time domain representations, may provide more useful Decomposition in the case where signal components overlap in frequency. The combined use of the EMD for both time and frequency domain representations of a signal is capable of generating more desirable signal Decompositions for nonstationary signals. The results of the time-frequency EMD on two example signals shows improvement in nonstationary signal separation with little loss of desirable Decomposition performance measures such as IMF orthogonality.

  • A joint time-frequency empirical mode Decomposition for nonstationary signal separation
    2007 9th International Symposium on Signal Processing and Its Applications, 2007
    Co-Authors: N Stevenson, Mahmoud Mesbah, B. Boashash, H.j. Whitehouse
    Abstract:

    This paper outlines the application of the empirical mode Decomposition (EMD) to a frequency domain representation of a signal. The application to frequency domain representations, as opposed to time domain representations, may provide more useful Decomposition in the case where signal components overlap in frequency. The combined use of the EMD for both time and frequency domain representations of a signal is capable of generating more desirable signal Decompositions for nonstationary signals. The results of the time-frequency EMD on two example signals shows improvement in nonstationary signal separation with little loss of desirable Decomposition performance measures such as IMF orthogonality.