04422nam 22007935 450 991068256580332120250617170235.09783031264191303126419310.1007/978-3-031-26419-1(MiAaPQ)EBC7216769(Au-PeEL)EBL7216769(CKB)26271466700041(DE-He213)978-3-031-26419-1(PPN)269092587(EXLCZ)992627146670004120230316d2023 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierMachine Learning and Knowledge Discovery in Databases European Conference, ECML PKDD 2022, Grenoble, France, September 19–23, 2022, Proceedings, Part V /edited by Massih-Reza Amini, Stéphane Canu, Asja Fischer, Tias Guns, Petra Kralj Novak, Grigorios Tsoumakas1st ed. 2023.Cham :Springer Nature Switzerland :Imprint: Springer,2023.1 online resource (669 pages)Lecture Notes in Artificial Intelligence,2945-9141 ;13717Print version: Amini, Massih-Reza Machine Learning and Knowledge Discovery in Databases Cham : Springer International Publishing AG,c2023 9783031264184 Supervised learning -- Probabilistic inference -- Optimal transport -- Optimization -- Quantum, hardware -- Sustainability.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 ;13717Artificial intelligenceComputer scienceMathematicsComputersComputer engineeringComputer networksApplication softwareImage processingDigital techniquesComputer visionArtificial IntelligenceMathematics of ComputingComputing MilieuxComputer Engineering and NetworksComputer and Information Systems ApplicationsComputer Imaging, Vision, Pattern Recognition and GraphicsArtificial intelligence.Computer scienceMathematics.Computers.Computer engineering.Computer networks.Application software.Image processingDigital techniques.Computer vision.Artificial Intelligence.Mathematics of Computing.Computing Milieux.Computer Engineering and Networks.Computer and Information Systems Applications.Computer Imaging, Vision, Pattern Recognition and Graphics.006.31006.31Amini Massih-Reza1060956MiAaPQMiAaPQMiAaPQBOOK9910682565803321Machine learning and knowledge discovery in databases3406175UNINA