Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part V

The European Conference on Machine Learning and Knowledge Discovery in Databases,ECML PKDD 2022, held in Grenoble, France, had 236 full papers and 17 Demo Track contributions, covering various topics in machine learning and knowledge discovery. The papers were reviewed and selected from 1060 submissions.

Format: Paperback / softback
Length: 633 pages
Publication date: 17 March 2023
Publisher: Springer International Publishing AG

The multi-volume set LNAI 13713 until 13718, comprising the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2022), held in Grenoble, France, in September 2022, represents a comprehensive collection of cutting-edge research and insights. This conference, one of the premier events in the field, attracted a remarkable 1060 submissions, from which a select 236 full papers were carefully reviewed and accepted for inclusion in these proceedings.

The conference proceedings are organized into six topical sections, covering a wide range of machine learning and knowledge discovery topics. Part I explores clustering and dimensionality reduction, anomaly detection, interpretability and explainability, ranking and recommender systems, transfer and multitask learning, and more. Part II delves into networks and graphs, including knowledge graphs, social network analysis, graph neural networks, natural language processing and text mining, conversational systems, and more. Part III focuses on deep learning, robust and adversarial machine learning, generative models, computer vision, meta-learning, neural architecture search, and related areas. Part IV explores reinforcement learning, multi-agent reinforcement learning, bandits and online learning, active and semi-supervised learning, private and federated learning, and more. Part V explores supervised learning, probabilistic inference, optimal transport, optimization, quantum computing, sustainability, and related topics. Part VI focuses on time series analysis, financial machine learning, applications in transportation, and a demo track showcasing innovative projects and prototypes.

Each section is further divided into subsections, allowing for in-depth exploration of specific research areas. The contributions in these proceedings showcase the latest advancements and breakthroughs in machine learning and knowledge discovery, covering a diverse range of domains and applications. The authors, experts in their respective fields, have contributed their valuable research findings, providing valuable insights and directions for future research endeavors.

The multi-volume set LNAI 13713 until 13718 serves as a valuable resource for researchers, practitioners, and students in the field of machine learning and knowledge discovery. It provides a comprehensive overview of the state-of-the-art techniques, methodologies, and applications, fostering collaboration and advancing the knowledge of this rapidly evolving field.

Weight: 1027g
Dimension: 235 x 155 (mm)
ISBN-13: 9783031264184
Edition number: 1st ed. 2023