يعرض 1 - 10 نتائج من 281 نتيجة بحث عن '"Dataset shift"', وقت الاستعلام: 0.86s تنقيح النتائج
  1. 1
    دورية أكاديمية
    Dynamic Quantification With Constrained Error Under Unknown General Dataset Shift

    المؤلفون: Denham, B., Lai, E.M., Sinha, R., Naeem, M.A.

    المصدر: IEEE Transactions on Knowledge and Data Engineering IEEE Trans. Knowl. Data Eng. Knowledge and Data Engineering, IEEE Transactions on. 36(7):2980-2994 Jul, 2024

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  2. 2
    مؤتمر
    Feature Attribution Explanation to Detect Harmful Dataset Shift

    المؤلفون: Wang, Ziming, Huang, Changwu, Yao, Xin

    المصدر: 2023 International Joint Conference on Neural Networks (IJCNN) Neural Networks (IJCNN), 2023 International Joint Conference on. :1-8 Jun, 2023

    Relation: 2023 International Joint Conference on Neural Networks (IJCNN)

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  3. 3
    دورية أكاديمية
    Binary quantification and dataset shift: an experimental investigation

    المؤلفون: González, PabloAff1, IDs10618024010141_cor1, Moreo, Alejandro, Sebastiani, Fabrizio

    المصدر: Data Mining and Knowledge Discovery. 38(4):1670-1712

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  4. 4
    مؤتمر
    Detecting Distributional Shift Responsible for Predictive Model's Failure

    المؤلفون: Mukherjee, Dipanwita Sinha, Bhandari, Divyanshu, Yeri, Naveen Gururaja

    المصدر: 2022 International Conference for Advancement in Technology (ICONAT) Advancement in Technology (ICONAT),2022 International Conference for. :1-5 Jan, 2022

    Relation: 2022 International Conference for Advancement in Technology (ICONAT)

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  5. 5
    مؤتمر
    Gain-Some-Lose-Some: Reliable Quantification Under General Dataset Shift

    المؤلفون: Denham, Benjamin, Lai, Edmund M-K, Sinha, Roopak, Naeem, M. Asif

    المصدر: 2021 IEEE International Conference on Data Mining (ICDM) ICDM Data Mining (ICDM), 2021 IEEE International Conference on. :1048-1053 Dec, 2021

    Relation: 2021 IEEE International Conference on Data Mining (ICDM)

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  6. 6
    دورية أكاديمية
    Biquality learning: a framework to design algorithms dealing with closed-set distribution shifts

    المؤلفون: Nodet, PierreAff1, Aff3, IDs10994023063723_cor1, Lemaire, Vincent, Bondu, Alexis, Cornuéjols, Antoine

    المصدر: Machine Learning. 112(12):4663-4692

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  7. 7
    مؤتمر
    Decoupling Autoencoders for Robust One-vs-Rest Classification

    المؤلفون: Lubbering, Max, Gebauer, Michael, Ramamurthy, Rajkumar, Bauckhage, Christian, Sifa, Rafet

    المصدر: 2021 IEEE 8th International Conference on Data Science and Advanced Analytics (DSAA) Data Science and Advanced Analytics (DSAA), 2021 IEEE 8th International Conference on. :1-10 Oct, 2021

    Relation: 2021 IEEE 8th International Conference on Data Science and Advanced Analytics (DSAA)

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  8. 8
    مؤتمر
    A Model-Driven Engineering Approach for Monitoring Machine Learning Models

    المؤلفون: Kourouklidis, Panagiotis, Kolovos, Dimitris, Noppen, Joost, Matragkas, Nicholas

    المصدر: 2021 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C) MODELS-C Model Driven Engineering Languages and Systems Companion (MODELS-C), 2021 ACM/IEEE International Conference on. :160-164 Oct, 2021

    Relation: 2021 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C)

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  9. 9
    مؤتمر
    Detection of Dataset Shifts in Learning-Enabled Cyber-Physical Systems using Variational Autoencoder for Regression

    المؤلفون: Cai, Feiyang, Ozdagli, Ali I., Koutsoukos, Xenofon

    المصدر: 2021 4th IEEE International Conference on Industrial Cyber-Physical Systems (ICPS) Industrial Cyber-Physical Systems (ICPS), 2021 4th IEEE International Conference on. :104-111 May, 2021

    Relation: 2021 4th IEEE International Conference on Industrial Cyber-Physical Systems (ICPS)

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  10. 10
    دورية أكاديمية
    An evaluation of Deep Learning based stereo dense matching dataset shift from aerial images and a large scale stereo dataset

    المؤلفون: Teng Wu, Bruno Vallet, Marc Pierrot-Deseilligny, Ewelina Rupnik

    المصدر: International Journal of Applied Earth Observations and Geoinformation, Vol 128, Iss , Pp 103715- (2024)

    مصطلحات موضوعية: Stereo-dense matching, Deep learning, Benchmarking, Dataset shift, LiDAR processing, 3D reconstruction, Physical geography, GB3-5030, Environmental sciences, GE1-350

    وصف الملف: electronic resource

    Relation: http://www.sciencedirect.com/science/article/pii/S1569843224000694; https://doaj.org/toc/1569-8432

    URL الوصول: https://doaj.org/article/1fa634b59f90486fb7d990f896b6a344

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