LEADER 03412nam 2200529 450 001 9910682562603321 005 20230729144125.0 010 $a3-031-26387-1 024 7 $a10.1007/978-3-031-26387-3 035 $a(MiAaPQ)EBC7216781 035 $a(Au-PeEL)EBL7216781 035 $a(CKB)26271473600041 035 $a(DE-He213)978-3-031-26387-3 035 $a(PPN)269092552 035 $a(EXLCZ)9926271473600041 100 $a20230729d2023 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aMachine learning and knowledge discovery in databases $eEuropean conference, ECML PKDD 2022, Grenoble, France, September 19-23, 2022, proceedings, Part I /$fedited by Massih-Reza Amini [and five others] 205 $a1st ed. 2023. 210 1$aCham, Switzerland :$cSpringer Nature Switzerland AG,$d[2023] 210 4$dİ2023 215 $a1 online resource (768 pages) 225 1 $aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v13713 311 08$aPrint version: Amini, Massih-Reza Machine Learning and Knowledge Discovery in Databases Cham : Springer International Publishing AG,c2023 9783031263866 320 $aIncludes bibliographical references and index. 327 $aClustering and dimensionality reduction -- anomaly detection -- interpretability and explainability -- ranking and recommender systems -- transfer and multitask learning. 330 $aThe multi-volume set LNAI 13713 until 13718 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2022, which took place in Grenoble, France, in September 2022. The 236 full papers presented in these proceedings were carefully reviewed and selected from a total of 1060 submissions. In addition, the proceedings include 17 Demo Track contributions. The volumes are organized in topical sections as follows: Part I: Clustering and dimensionality reduction; anomaly detection; interpretability and explainability; ranking and recommender systems; transfer and multitask learning; Part II: Networks and graphs; knowledge graphs; social network analysis; graph neural networks; natural language processing and text mining; conversational systems; Part III: Deep learning; robust and adversarial machine learning; generative models; computer vision; meta-learning, neural architecture search; Part IV: Reinforcement learning; multi-agent reinforcement learning; bandits and online learning; active and semi-supervised learning; private and federated learning; . Part V: Supervised learning; probabilistic inference; optimal transport; optimization; quantum, hardware; sustainability; Part VI: Time series; financial machine learning; applications; applications: transportation; demo track. 410 0$aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v13713 606 $aData mining$vCongresses 606 $aDatabases$vCongresses 606 $aMachine learning$vCongresses 615 0$aData mining 615 0$aDatabases 615 0$aMachine learning 676 $a006.31 702 $aAmini$b Massih-Reza 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910682562603321 996 $aMachine Learning and Knowledge Discovery in Databases$9773712 997 $aUNINA