04236nam 22007455 450 991068256790332120250617170235.09783031264092303126409610.1007/978-3-031-26409-2(MiAaPQ)EBC7216744(Au-PeEL)EBL7216744(CKB)26271187800041(DE-He213)978-3-031-26409-2(PPN)269092595(EXLCZ)992627118780004120230316d2023 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierMachine Learning and Knowledge Discovery in Databases European Conference, ECML PKDD 2022, Grenoble, France, September 19–23, 2022, Proceedings, Part III /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 (722 pages)Lecture Notes in Artificial Intelligence,2945-9141 ;13715Print version: Amini, Massih-Reza Machine Learning and Knowledge Discovery in Databases Cham : Springer International Publishing AG,c2023 9783031264085 Deep learning -- robust and adversarial machine learning -- generative models -- computer vision -- meta-learning, neural architecture search.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 ;13715Artificial intelligenceComputer scienceMathematicsComputer visionComputer networksComputers, Special purposeComputer engineeringArtificial IntelligenceMathematics of ComputingComputer VisionComputer Communication NetworksSpecial Purpose and Application-Based SystemsComputer Engineering and NetworksArtificial intelligence.Computer scienceMathematics.Computer vision.Computer networks.Computers, Special purpose.Computer engineering.Artificial Intelligence.Mathematics of Computing.Computer Vision.Computer Communication Networks.Special Purpose and Application-Based Systems.Computer Engineering and Networks.006.3006.31Amini Massih-Reza1060956MiAaPQMiAaPQMiAaPQBOOK9910682567903321Machine learning and knowledge discovery in databases3406175UNINA