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

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 topics such as clustering, dimensionality reduction, anomaly detection, interpretability, ranking, recommender systems, transfer and multitask learning, networks and graphs, knowledge graphs, social network analysis, graph neural networks, natural language processing, text mining, conversational systems, deep learning, robust and adversarial machine learning, generative models, computer vision, meta-learning, neural architecture search, reinforcement learning, multi-agent reinforcement learning, bandits and online learning, active and semi-supervised learning, private and federated learning, supervised learning, probabilistic inference, optimal transport, optimization, quantum, hardware, sustainability, and time series.

Format: Paperback / softback
Length: 683 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 of machine learning and knowledge discovery, attracted a remarkable 1060 submissions, from which a select 236 full papers were carefully reviewed and accepted for inclusion in these proceedings.

In addition to the full papers, the proceedings feature 17 Demo Track contributions, showcasing innovative applications and technologies in the field. The volumes are organized into six topical sections, covering a wide range of machine learning and knowledge discovery topics:

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

These sections encompass a diverse range of machine learning techniques and applications, reflecting the latest advancements and developments in the field. The contributions in LNAI 13713 until 13718 provide valuable insights into the state-of-the-art methodologies, algorithms, and applications that are driving innovation across industries and academia.

The conference's success is a testament to the growing importance of machine learning and knowledge discovery in databases, as well as the vibrant research community that continues to push the boundaries of this field. The proceedings serve as a valuable resource for researchers, practitioners, and students interested in advancing their understanding and expertise in machine learning and knowledge discovery.

Whether you are a seasoned researcher or just starting your journey in this domain, LNAI 13713 until 13718 is a must-read for anyone seeking to stay at the forefront of this rapidly evolving field.

Weight: 1104g
Dimension: 235 x 155 (mm)
ISBN-13: 9783031264085
Edition number: 1st ed. 2023