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020 _a9783030865238
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024 7 _a10.1007/978-3-030-86523-8
_2doi
050 4 _aQ334-342
050 4 _aTA347.A78
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072 7 _aCOM004000
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245 1 0 _aMachine Learning and Knowledge Discovery in Databases. Research Track
_h[electronic resource] :
_bEuropean Conference, ECML PKDD 2021, Bilbao, Spain, September 13-17, 2021, Proceedings, Part III /
_cedited by Nuria Oliver, Fernando Pérez-Cruz, Stefan Kramer, Jesse Read, Jose A. Lozano.
250 _a1st ed. 2021.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2021.
300 _aXXXV, 831 p. 239 illus., 226 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v12977
520 _aThe multi-volume set LNAI 12975 until 12979 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2021, which was held during September 13-17, 2021. The conference was originally planned to take place in Bilbao, Spain, but changed to an online event due to the COVID-19 pandemic. The 210 full papers presented in these proceedings were carefully reviewed and selected from a total of 869 submissions. The volumes are organized in topical sections as follows: Research Track: Part I: Online learning; reinforcement learning; time series, streams, and sequence models; transfer and multi-task learning; semi-supervised and few-shot learning; learning algorithms and applications. Part II: Generative models; algorithms and learning theory; graphs and networks; interpretation, explainability, transparency, safety. Part III: Generative models; search and optimization; supervised learning; text mining and natural language processing; image processing, computer vision and visual analytics. Applied Data Science Track: Part IV: Anomaly detection and malware; spatio-temporal data; e-commerce and finance; healthcare and medical applications (including Covid); mobility and transportation. Part V: Automating machine learning, optimization, and feature engineering; machine learning based simulations and knowledge discovery; recommender systems and behavior modeling; natural language processing; remote sensing, image and video processing; social media.
650 0 _aArtificial intelligence.
_93407
650 0 _aSocial sciences
_xData processing.
_983360
650 0 _aData mining.
_93907
650 0 _aNumerical analysis.
_94603
650 0 _aComputer vision.
_9111847
650 1 4 _aArtificial Intelligence.
_93407
650 2 4 _aComputer Application in Social and Behavioral Sciences.
_931815
650 2 4 _aData Mining and Knowledge Discovery.
_9111848
650 2 4 _aNumerical Analysis.
_94603
650 2 4 _aComputer Vision.
_9111849
700 1 _aOliver, Nuria.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9111850
700 1 _aPérez-Cruz, Fernando.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9111851
700 1 _aKramer, Stefan.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9111852
700 1 _aRead, Jesse.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9111853
700 1 _aLozano, Jose A.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9111854
710 2 _aSpringerLink (Online service)
_9111855
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783030865221
776 0 8 _iPrinted edition:
_z9783030865245
830 0 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v12977
_9111856
856 4 0 _uhttps://doi.org/10.1007/978-3-030-86523-8
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