Axis 1: Data valuation for decision making
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413 results — page 12 of 21
We consider an inventory routing problem in discrete time where a supplier has to serve a set of customers over a time horizon. A capacity constraint for th...
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A profit and a demand are associated with each arc of a set of profitable arcs of a given graph. A travel time is associated with each arc of the graph. A fl...
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<p> The complementarity of two renewable energy sources, namely hydro and wind, is investigated. We consider the diversification effect of wind power to re...
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Tree based methods have not yet been adapted to handle mixed effects. Previous works extending them to accommodate correlated data are based on the multivari...
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A magnet is a pair <i>u,v</i> of adjacent vertices such that the proper neighbours of <i>u</i> are completely linked to the proper neighbours of <i>v</i>. It...
BibTeX referenceEstimation from Aggregate Data
This work proposes a statistical methodology to handle aggregate data. Aggregate data arises in many fields such as medical science, ecology, social science,...
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This research assesses the impact of the various states of mind of Flow psychological theory (Csíkszentmihályi 1990) in relation to brand recall and recognit...
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This paper presents a model for identifying general goals of anonymous consumers visiting a retail website. When visiting a transactional website, consumers ...
BibTeX referencePerformance of n-Grams for a Question Retrieval System in the Context of Approximated Spelling
Question retrieval systems, unlike question answering systems, exploit the knowledge contained in previously answered questions to answer new ones by returni...
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There has been a wide interest to extend univariate and multivariate nonparametric procedures to clustered and hierarchical data. Traditionally, parametric m...
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Top-tier customers - that is, those 20% of customers that typically bring in 80% of all profits - are extremely valuable to companies. In the many instances ...
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Variable neighborhood search (VNS) is a metaheuristic, or framework for building heuristics, based upon systematic change of neighborhoods both in a decent ...
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Minimum sum-of-squares clustering (MSSC) consists in partitioning a given set of <i>n</i> points into <i>k</i> clusters in order to minimize the sum of squar...
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This paper estimates a structural vector autoregression model to assess the dynamic effects of terrorism on output and prices in Israel over the post-1985 pe...
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Methods, models, heuristic and exact algorithms for clustering are reviewed from a mathematical programming view point.
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A recent proof of NP-hardness of Euclidean sum-of-squares clustering, due to Drineas et al., <i>Machine Learning</i> 56, 9--33, 2004, is not valid. An altern...
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Le texte qui suit est un chapitre du livre intitulé <i>Fourmis artificielles, des bases algorithmiques aux concepts et réalisations avancés</i>, Nicolas Monm...
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Minimum sum-of-squares clustering consists in partitioning a given set of <i>n</i> points into <i>c</i> clusters in order to minimize the sum of squared dist...
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In this paper we present a simple technique that uses background information to improve mining the frequent patterns of structured data. This technique uses ...
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Flexibility in workforce planning is one of the best ways to respond to fluctuations of the demand. This paper proposes a flexible mixed integer linear pro...
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