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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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    • G06K9/6267Classification techniques
    • G06K9/6279Classification techniques relating to the number of classes
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
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    • G06K9/6201Matching; Proximity measures
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    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
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    • G06K9/6261Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation partitioning the feature space
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    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6217Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G06K9/6262Validation, performance evaluation or active pattern learning techniques
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
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    • G06F17/30286Information retrieval; Database structures therefor; File system structures therefor in structured data stores
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    • G06Q30/00Commerce, e.g. shopping or e-commerce

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