TY  - BOOK
AU  - Amini,Massih-Reza
AU  - Canu,Stéphane
AU  - Fischer,Asja
AU  - Guns,Tias
AU  - Kralj Novak,Petra
AU  - Tsoumakas,Grigorios
ED  - SpringerLink (Online service)
TI  - Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part IV 
T2  - Lecture Notes in Artificial Intelligence,
SN  - 9783031264122
AV  - Q334-342 
U1  - 006.3 23
PY  - 2023///
CY  - Cham
PB  - Springer Nature Switzerland, Imprint: Springer
KW  - Artificial intelligence
KW  - Education
KW  - Data processing
KW  - Computer engineering
KW  - Computer networks 
KW  - Social sciences
KW  - Computer science
KW  - Mathematics
KW  - Image processing
KW  - Digital techniques
KW  - Computer vision
KW  - Artificial Intelligence
KW  - Computers and Education
KW  - Computer Engineering and Networks
KW  - Computer Application in Social and Behavioral Sciences
KW  - Mathematics of Computing
KW  - Computer Imaging, Vision, Pattern Recognition and Graphics
N1  - Acceso multiusuario; Reinforcement learning -- Multi-agent reinforcement learning -- Bandits and online learning -- Active and semi-supervised learning -- Private and federated learning
N2  - 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
UR  - http://libcon.rec.uabc.mx:2048/login?url=https://doi.org/10.1007/978-3-031-26412-2
ER  -