Machine Learning and Knowledge Discovery in Databases
Springer International Publishing (Verlag)
978-3-031-26411-5 (ISBN)
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.
Reinforcement learning.- Multi-agent reinforcement learning.- Bandits and online learning.- Active and semi-supervised learning.- Private and federated learning.
Erscheinungsdatum | 18.03.2023 |
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Reihe/Serie | Lecture Notes in Artificial Intelligence | Lecture Notes in Computer Science |
Zusatzinfo | XLVI, 641 p. 142 illus., 133 illus. in color. |
Verlagsort | Cham |
Sprache | englisch |
Maße | 155 x 235 mm |
Gewicht | 1024 g |
Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
Schlagworte | Applications • Artificial Intelligence • Autonomous Agents • Computer Networks • Computer Science • Computer Security • Computer systems • conference proceedings • Correlation Analysis • Data Mining • Education • Engineering • Image Processing • Informatics • Intelligent Agents • Internet • learning • machine learning • Mathematics • multiagent system • Research |
ISBN-10 | 3-031-26411-8 / 3031264118 |
ISBN-13 | 978-3-031-26411-5 / 9783031264115 |
Zustand | Neuware |
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