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Titlebook: Machine Learning and Principles and Practice of Knowledge Discovery in Databases; International Worksh Irena Koprinska,Paolo Mignone,Sepide

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發(fā)表于 2025-3-21 16:50:40 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Machine Learning and Principles and Practice of Knowledge Discovery in Databases
副標(biāo)題International Worksh
編輯Irena Koprinska,Paolo Mignone,Sepideh Pashami
視頻videohttp://file.papertrans.cn/621/620573/620573.mp4
叢書名稱Communications in Computer and Information Science
圖書封面Titlebook: Machine Learning and Principles and Practice of Knowledge Discovery in Databases; International Worksh Irena Koprinska,Paolo Mignone,Sepide
描述This volume constitutes the papers of several workshops which were held in conjunction with the International Workshops of ECML PKDD 2022 on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2022, held in Grenoble, France, during September 19–23, 2022.?.The 73 revised full papers and 6 short papers presented in this book were carefully reviewed and selected from 143 submissions. ECML PKDD 2022 presents the following workshops:.Workshop on Data Science for Social Good (SoGood 2022).Workshop on New Frontiers in Mining Complex Patterns (NFMCP 2022).Workshop on Explainable Knowledge Discovery in Data Mining (XKDD 2022).Workshop on Uplift Modeling (UMOD 2022).Workshop on IoT, Edge and Mobile for Embedded Machine Learning (ITEM 2022).Workshop on Mining Data for Financial Application (MIDAS 2022).Workshop on Machine Learning for Cybersecurity (MLCS 2022).Workshop on Machine Learning for Buildings Energy Management (MLBEM 2022).?.Workshop on Machine Learning for Pharma and Healthcare Applications (PharML 2022).Workshop on Data Analysis in Life Science (DALS 2022).Workshop on IoT Streams for Predictive Maintenance (IoT-PdM 2022).
出版日期Conference proceedings 2023
關(guān)鍵詞artificial intelligence; bayesian networks; computer networks; computer vision; data mining; databases; fu
版次1
doihttps://doi.org/10.1007/978-3-031-23618-1
isbn_softcover978-3-031-23617-4
isbn_ebook978-3-031-23618-1Series ISSN 1865-0929 Series E-ISSN 1865-0937
issn_series 1865-0929
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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1865-0929 tions (PharML 2022).Workshop on Data Analysis in Life Science (DALS 2022).Workshop on IoT Streams for Predictive Maintenance (IoT-PdM 2022).978-3-031-23617-4978-3-031-23618-1Series ISSN 1865-0929 Series E-ISSN 1865-0937
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Gil Emmanuel Bancud,Alex John Labanon,Neil Angelo Abreo,Vladimer Kobayashi
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Sónia Teixeira,Bruno Veloso,José Coelho Rodrigues,Jo?o Gama
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Gender Stereotyping Impact in?Facial Expression Recognitionerlooked so far, it is important to understand the impact it may have in the context of FER. To do so, we use a popular FER dataset, FER+, to generate derivative datasets with different amounts of stereotypical bias by altering the gender proportions of certain labels. We then proceed to measure the
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A Unified Framework for?Assessing Energy Efficiency of?Machine Learningel system, we also introduce a concept for visually communicating efficiency information to the public in a comprehensible way. We apply our methods to over 20 SOTA models on a range of hardware architectures, giving an overview of the modern ML efficiency landscape.
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