1 option
Machine Learning and Knowledge Discovery in Databases : European Conference, ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part V / edited by Massih-Reza Amini, Stéphane Canu, Asja Fischer, Tias Guns, Petra Kralj Novak, Grigorios Tsoumakas.
- Format:
- Book
- Series:
- Computer Science (SpringerNature-11645)
- Lecture notes in computer science. Lecture notes in artificial intelligence 2945-9141 ; 13717
- Lecture Notes in Artificial Intelligence, 2945-9141 ; 13717
- Language:
- English
- Subjects (All):
- Artificial intelligence.
- Computer science-Mathematics.
- Computers.
- Computer engineering.
- Computer networks.
- Application software.
- Image processing-Digital techniques.
- Computer vision.
- Artificial Intelligence.
- Mathematics of Computing.
- Computing Milieux.
- Computer Engineering and Networks.
- Computer and Information Systems Applications.
- Computer Imaging, Vision, Pattern Recognition and Graphics.
- Local Subjects:
- Artificial Intelligence.
- Mathematics of Computing.
- Computing Milieux.
- Computer Engineering and Networks.
- Computer and Information Systems Applications.
- Computer Imaging, Vision, Pattern Recognition and Graphics.
- Physical Description:
- 1 online resource (XLVI, 633 pages) : 163 illustrations, 140 illustrations in color.
- Edition:
- 1st ed. 2023.
- Contained In:
- Springer Nature eBook
- Place of Publication:
- Cham : Springer Nature Switzerland : Imprint: Springer, 2023.
- System Details:
- text file PDF
- Summary:
- 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.
- Contents:
- Supervised learning
- Probabilistic inference
- Optimal transport
- Optimization
- Quantum, hardware
- Sustainability.
- Other Format:
- Printed edition:
- ISBN:
- 978-3-031-26419-1
- 9783031264191
- Access Restriction:
- Restricted for use by site license.
The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.