03343nam 2200517 450 99651775380331620230729144202.03-031-26390-110.1007/978-3-031-26390-3(MiAaPQ)EBC7216757(Au-PeEL)EBL7216757(CKB)26271463000041(DE-He213)978-3-031-26390-3(PPN)269092579(EXLCZ)992627146300004120230729d2023 uy 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierMachine learning and knowledge discovery in databases European conference, ECML PKDD 2022, Grenoble, France, September 19-23, 2022, proceedings, Part II /Massih-Reza Amini [and five others]1st ed. 2023.Cham, Switzerland :Springer Nature Switzerland AG,[2023]©20231 online resource (797 pages)Lecture Notes in Artificial Intelligence,2945-9141 ;13714Print version: Amini, Massih-Reza Machine Learning and Knowledge Discovery in Databases Cham : Springer International Publishing AG,c2023 9783031263897 Networks and graphs -- knowledge graphs -- social network analysis -- graph neural networks -- natural language processing and text mining -- conversational systems.The 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.Lecture Notes in Artificial Intelligence,2945-9141 ;13714Data miningCongressesDatabasesCongressesMachine learningCongressesData miningDatabasesMachine learning006.31Amini Massih-Reza1060956MiAaPQMiAaPQMiAaPQBOOK996517753803316Machine learning and knowledge discovery in databases3406175UNISA