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Li et al., 2018 - Google Patents

Data-driven ranking and selection: High-dimensional covariates and general dependence

Li et al., 2018

Document ID
14276442028815480161
Author
Li X
Zhang X
Zheng Z
Publication year
Publication venue
2018 Winter Simulation Conference (WSC)

External Links

Snippet

This paper considers the problem of ranking and selection with covariates and aims to identify a decision rule that stipulates the best alternative as a function of the observable covariates. We propose a general data-driven framework to accommodate (i) high …
Continue reading at ieeexplore.ieee.org (other versions)

Classifications

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    • G06K9/6279—Classification techniques relating to the number of classes
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    • G06K9/6232—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
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