Axis 1: Data valuation for decision making

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Cahiers du GERAD

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Optimal stopping is the problem of deciding the right time at which to take a particular action in a stochastic system, in order to maximize an expected rewa...

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A coloring of a graph is an assignment of colors to its vertices such that adjacent vertices have different colors. Two colorings are equivalent if they indu...

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A training-image free, high-order sequential simulation method is proposed herein, which is based on the efficient inference of high-order spatial statistics...

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We study the average number \(A(G)\) of colors in the non-equivalent colorings of a graph \(G\). We show some general properties of this graph invariant ...

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The Bell numbers count the number of different ways to partition a set of \(n\) elements while the graphical Bell numbers count the number of non-equivalen...

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We empirically test the prediction of Pastor, stambaugh, and Taylor (2020) that green firms outperform brown firms when concerns about climate change increas...

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Scholars and practitioners have long recognised the importance of data-driven operations and supply chain management (OSCM), which typically centres on produ...

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We consider the problem of designing vehicle routes in a distribution system that are at the same time cost-effective and visually attractive. In this pape...

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This paper studies disjunctive cutting planes in Mixed-Integer Conic Programming. Building on conic duality, we formulate a cut-generating conic program for...

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Data acquisition and recording in the form of databases are routine operations. The process of collecting data, however, may experience irregularities, res...

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Conditional estimation given specific covariate values (i.e., local conditional estimation or functional estimation) is ubiquitously useful with applications...

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Let \(G=(V,E)\) be a graph and let \(S\subseteq V\) be a subset of its vertices. If the subgraph of \(G\) induced by \(V\setminus S\) is acyclic, the...

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Artificial Intelligence (AI) is the next society transformation builder. Massive AI-based applications include cloud servers, cell phones, cars, and pandemic...

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The determinantal point process (DPP) provides a promising and attractive alternative to simple random sampling in cluster analysis or classification, for th...

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The crew pairing problem is generally modelled as a set partitioning problem where the flights have to be partitioned in pairings. A pairing is a sequence of...

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With sufficient layers, enough training data, enough time, and often a custom tailored architecture, modern deep learning methods can be extremely successf...

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Deploying applications having many processes in a multi-cloud environment is challenging. The cloud manager has goals such as minimizing power consumption, w...

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Clustering algorithms help identify homogeneous subgroups from data. In some cases, additional information about the relationship among some subsets of the d...

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A highly influential ingredient of many techniques designed to exploit sparsity in numerical optimization is the so-called chordal extension of a graph repre...

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We introduce the conditional \(p\)-dispersion problem (c-pDP), an incremental variant of the \(p\)-dispersion problem (pDP). In the c-pDP, one is given a...

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