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245 1 0 _aMachine Learning and Knowledge Discovery in Databases
_h[electronic resource] :
_bEuropean Conference, ECML PKDD 2022, Grenoble, France, September 19–23, 2022, Proceedings, Part IV /
_cedited by Massih-Reza Amini, Stéphane Canu, Asja Fischer, Tias Guns, Petra Kralj Novak, Grigorios Tsoumakas.
250 _a1st ed. 2023.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2023.
300 _aXLVI, 641 p. 142 illus., 133 illus. in color.
_bonline resource.
336 _atext
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337 _acomputer
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338 _aonline resource
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490 1 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v13716
505 0 _aReinforcement learning -- Multi-agent reinforcement learning -- Bandits and online learning -- Active and semi-supervised learning -- Private and federated learning.
520 _aThe multi-volume set LNAI 13713 until 13718 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2022, which took place in Grenoble, France, in September 2022. The 236 full papers presented in these proceedings were carefully reviewed and selected from a total of 1060 submissions. In addition, the proceedings include 17 Demo Track contributions. The volumes are organized in topical sections as follows: Part I: Clustering and dimensionality reduction; anomaly detection; interpretability and explainability; ranking and recommender systems; transfer and multitask learning; Part II: Networks and graphs; knowledge graphs; social network analysis; graph neural networks; natural language processing and text mining; conversational systems; Part III: Deep learning; robust and adversarial machine learning; generative models; computer vision; meta-learning, neural architecture search; Part IV: Reinforcement learning; multi-agent reinforcement learning; bandits and online learning; active and semi-supervised learning; private and federated learning; Part V: Supervised learning; probabilistic inference; optimal transport; optimization; quantum, hardware; sustainability; Part VI: Time series; financial machine learning; applications; applications: transportation; demo track.
650 0 _aArtificial intelligence.
650 0 _aEducation
_xData processing.
650 0 _aComputer engineering.
650 0 _aComputer networks .
650 0 _aSocial sciences
_xData processing.
650 0 _aComputer science
_xMathematics.
650 0 _aImage processing
_xDigital techniques.
650 0 _aComputer vision.
650 1 4 _aArtificial Intelligence.
650 2 4 _aComputers and Education.
650 2 4 _aComputer Engineering and Networks.
650 2 4 _aComputer Application in Social and Behavioral Sciences.
650 2 4 _aMathematics of Computing.
650 2 4 _aComputer Imaging, Vision, Pattern Recognition and Graphics.
700 1 _aAmini, Massih-Reza.
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700 1 _aCanu, Stéphane.
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700 1 _aFischer, Asja.
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700 1 _aGuns, Tias.
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700 1 _aKralj Novak, Petra.
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700 1 _aTsoumakas, Grigorios.
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710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
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776 0 8 _iPrinted edition:
_z9783031264139
830 0 _aLecture Notes in Artificial Intelligence,
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856 4 0 _uhttps://doi.org/10.1007/978-3-031-26412-2
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