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Machine learning and principles and ...
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Kamp, Michael.
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Machine learning and principles and practice of knowledge discovery in databases = international workshops of ECML PKDD 2021, virtual event, September 13-17, 2021 : proceedings.. Part I /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Machine learning and principles and practice of knowledge discovery in databases/ edited by Michael Kamp ... [et al.].
其他題名:
international workshops of ECML PKDD 2021, virtual event, September 13-17, 2021 : proceedings.
其他題名:
ECML PKDD 2021
其他作者:
Kamp, Michael.
出版者:
Cham :Springer International Publishing : : 2021.,
面頁冊數:
1 online resource (xxv, 882 p.) :ill. (chiefly col.), digital ;24 cm.
內容註:
Advances in Interpretable Machine Learning and Artificial Intelligence -- Parallel, Distributed, and Federated Learning -- Graph Embedding and Mining -- Machine Learning for Irregular Time Series -- IoT, Edge, and Mobile for Embedded Machine Learning -- eXplainable Knowledge Discovery in Data Mining -- Bias and Fairness in AI -- International Workshop on Active Inference.
Contained By:
Springer Nature eBook
標題:
Machine learning - Congresses. -
電子資源:
https://doi.org/10.1007/978-3-030-93736-2
ISBN:
9783030937362
Machine learning and principles and practice of knowledge discovery in databases = international workshops of ECML PKDD 2021, virtual event, September 13-17, 2021 : proceedings.. Part I /
Machine learning and principles and practice of knowledge discovery in databases
international workshops of ECML PKDD 2021, virtual event, September 13-17, 2021 : proceedings.Part I /[electronic resource] :ECML PKDD 2021edited by Michael Kamp ... [et al.]. - Cham :Springer International Publishing :2021. - 1 online resource (xxv, 882 p.) :ill. (chiefly col.), digital ;24 cm. - Communications in computer and information science,15241865-0937 ;. - Communications in computer and information science ;1524..
Advances in Interpretable Machine Learning and Artificial Intelligence -- Parallel, Distributed, and Federated Learning -- Graph Embedding and Mining -- Machine Learning for Irregular Time Series -- IoT, Edge, and Mobile for Embedded Machine Learning -- eXplainable Knowledge Discovery in Data Mining -- Bias and Fairness in AI -- International Workshop on Active Inference.
This two-volume set constitutes the refereed proceedings of the workshops which complemented the 21th Joint European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD, held in September 2021. Due to the COVID-19 pandemic the conference and workshops were held online. The 104 papers were thoroughly reviewed and selected from 180 papers submited for the workshops. This two-volume set includes the proceedings of the following workshops: Workshop on Advances in Interpretable Machine Learning and Artificial Intelligence (AIMLAI 2021) Workshop on Parallel, Distributed and Federated Learning (PDFL 2021) Workshop on Graph Embedding and Mining (GEM 2021) Workshop on Machine Learning for Irregular Time-series (ML4ITS 2021) Workshop on IoT, Edge, and Mobile for Embedded Machine Learning (ITEM 2021) Workshop on eXplainable Knowledge Discovery in Data Mining (XKDD 2021) Workshop on Bias and Fairness in AI (BIAS 2021) Workshop on Workshop on Active Inference (IWAI 2021) Workshop on Machine Learning for Cybersecurity (MLCS 2021) Workshop on Machine Learning in Software Engineering (MLiSE 2021) Workshop on MIning Data for financial applications (MIDAS 2021) Sixth Workshop on Data Science for Social Good (SoGood 2021) Workshop on Machine Learning for Pharma and Healthcare Applications (PharML 2021) Second Workshop on Evaluation and Experimental Design in Data Mining and Machine Learning (EDML 2020) Workshop on Machine Learning for Buildings Energy Management (MLBEM 2021)
ISBN: 9783030937362
Standard No.: 10.1007/978-3-030-93736-2doiSubjects--Topical Terms:
576368
Machine learning
--Congresses.
LC Class. No.: Q325.5 / M33 2021
Dewey Class. No.: 006.31
Machine learning and principles and practice of knowledge discovery in databases = international workshops of ECML PKDD 2021, virtual event, September 13-17, 2021 : proceedings.. Part I /
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