يعرض 1 - 3 نتائج من 3 نتيجة بحث عن '"Synthetic Data Quality."', وقت الاستعلام: 0.44s تنقيح النتائج
  1. 1
    Dissertation/ Thesis
    Measuring the Utility of Synthetic Data : An Empirical Evaluation of Population Fidelity Measures as Indicators of Synthetic Data Utility in Classification Tasks
    Mätning av Användbarheten hos Syntetiska Data : En Empirisk Utvärdering av Population Fidelity mätvärden som Indikatorer på Syntetiska Datas Användbarhet i Klassifikationsuppgifter

    المؤلفون: Florean, Alexander

    مصطلحات موضوعية: Synthetic Data, Machine Learning, Population Fidelity Measures, Utility Metrics, Synthetic Data Quality Evaluation, Classification Algorithms, Utility Estimation, Data Privacy, Artificial Intelligence, Experiment Framework, Model Performance Assessment, Syntetisk Data, Maskininlärning, Population Fidelity Mätvärden, Användbarhetsmätvärden, Kvalitetsutvärdering av Syntetisk Data, Klassificeringsalgoritmer, Användbarhetsutvärdering, Dataintegritet, Artificiell Intelligens, AI, Experiment Ramverk, Utvärdering av Modellprestanda, Computer Sciences, Datavetenskap (datalogi)

    وصف الملف: application/pdf

    الاتاحة: http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-98405

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  2. 2
    Dissertation/ Thesis
    Measuring the Utility of Synthetic Data : An Empirical Evaluation of Population Fidelity Measures as Indicators of Synthetic Data Utility in Classification Tasks ; Mätning av Användbarheten hos Syntetiska Data : En Empirisk Utvärdering av Population Fidelity mätvärden som Indikatorer på Syntetiska Datas Användbarhet i Klassifikationsuppgifter

    المؤلفون: Florean, Alexander

    مصطلحات موضوعية: Synthetic Data, Machine Learning, Population Fidelity Measures, Utility Metrics, Synthetic Data Quality Evaluation, Classification Algorithms, Utility Estimation, Data Privacy, Artificial Intelligence, Experiment Framework, Model Performance Assessment, Syntetisk Data, Maskininlärning, Population Fidelity Mätvärden, Användbarhetsmätvärden, Kvalitetsutvärdering av Syntetisk Data, Klassificeringsalgoritmer, Användbarhetsutvärdering, Dataintegritet, Artificiell Intelligens, AI, Experiment Ramverk, Utvärdering av Modellprestanda, Computer Sciences, Datavetenskap (datalogi)

    وصف الملف: application/pdf

    الاتاحة: http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-98405

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  3. 3
    Conference
    Exploring the Faithfulness of Synthetic Data by Generative Models

    المؤلفون: Fiammetta Marulli, Pierluigi Paganini, Fabio Lancellotti

    المساهمون: IEEE Computer Society Conference Publishing Services, Marulli, Fiammetta, Paganini, Pierluigi, Lancellotti, Fabio

    مصطلحات موضوعية: Generative models, Generative Adversarial Networks, Data Augmentation, Data Quality Metrics, Synthetic Data Quality.

    Relation: info:eu-repo/semantics/altIdentifier/isbn/979-8-3503-4534-6; ispartofbook:2023 International Conference on Machine Learning and Applications (ICMLA 2023) Proceedings; 2023 International Conference on Machine Learning and Applications; volume:1; firstpage:2214; lastpage:2221; numberofpages:8; https://hdl.handle.net/11591/519972; https://conferences.computer.org/icmlapub23/pdfs/ICMLA2023-5c7aMwQuVPRWIchNJyGdNb/453400c214/453400c214.pdf

    الاتاحة: https://hdl.handle.net/11591/519972
    https://conferences.computer.org/icmlapub23/pdfs/ICMLA2023-5c7aMwQuVPRWIchNJyGdNb/453400c214/453400c214.pdf

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