Skip to search
Skip to main content
Title starts with
Author (sorted by title)
Call number (browse)
Princeton University Library Catalog
Machine learning and knowledge discovery in databases : European conference, ECML PKDD 2022, Grenoble, France, September 19-23, 2022, proceedings, Part V / Massih-Reza Amini [and five others].
1st ed. 2023.
Cham, Switzerland : Springer Nature Switzerland AG, 
1 online resource (669 pages)
Lecture Notes in Artificial Intelligence, 13717
[More in this series]
Lecture Notes in Artificial Intelligence, 2945-9141 ; 13717
[More in this series]
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.
Source of description
Description based on print version record.
Show 3 more Contents items
Statement on language in description
Princeton University Library aims to describe library materials in a manner that is respectful to the individuals and communities who create, use, and are represented in the collections we manage.
Ask a Question
Suggest a Correction
Report Harmful Language