Machine Learning and Knowledge Discovery in Databases / Lecture Notes in Computer Science Bd.13715 (PDF)
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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.
- 2023, 1st ed. 2023, 683 Seiten, Englisch
- Herausgegeben: Massih-Reza Amini, Stéphane Canu, Asja Fischer, Tias Guns, Petra Kralj Novak, Grigorios Tsoumakas
- Verlag: Springer International Publishing
- ISBN-10: 3031264096
- ISBN-13: 9783031264092
- Erscheinungsdatum: 16.03.2023
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
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- Größe: 55 MB
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