By Kevin Wilkins
This is a preview of subscription content, log in via an institution to check access. About this bookArtificial intelligence and expert systems have seen a great deal of research in recent years, much of which has been devoted to methods for incorporating uncertainty into models. This book is devoted to providing a thorough and up-to-date survey of this field for researchers and students.
The multi-volume set LNAI 14169 until 14175 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2023, which took place in Turin, Italy, in September 2023. The volumes are organized in topical sections as follows:Part I: Active Learning; Adversarial Machine Learning; Anomaly Detection; Applications; Bayesian Methods; Causality; Clustering. Computer Vision; Deep Learning; Fairness; Federated Learning; Few-shot learning; Generative Models; Graph Contrastive Learning. Part IV: Natural Language Processing; Neuro/Symbolic Learning; Optimization; Recommender Systems; Reinforcement Learning; Representation Learning. Part VI: Applied Machine Learning; Computational Social Sciences; Finance; Hardware and Systems; Healthcare & Bioinformatics; Human-Computer Interaction; Recommendation and Information Retrieval.
Lianyong Qi (IEEE Senior Member), received his Ph.D degree from the Department of Computer Science and Technology, Nanjing University, China. Now, he is a professor of the College of Computer Science and Technology, China University of Petroleum (East China), China. Liu Qi is a professor, doctoral supervisor and Vice Director of School of Software, Nanjing University of Information Science & Technology. Prof X. Liu received his PhD in Computer Science from De Montfort University and joined Napier in 1999. He is a senior member of IEEE Society and a member of British Computer Society.
