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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.
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.
| Erscheinungsjahr: | 2023 |
|---|---|
| Genre: | Informatik, Mathematik, Medizin, Naturwissenschaften, Technik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Taschenbuch |
| Reihe: | Lecture Notes in Computer Science |
| Inhalt: |
xlvi
641 S. 9 s/w Illustr. 133 farbige Illustr. 641 p. 142 illus. 133 illus. in color. |
| ISBN-13: | 9783031264115 |
| ISBN-10: | 3031264118 |
| Sprache: | Englisch |
| Einband: | Kartoniert / Broschiert |
| Redaktion: |
Amini, Massih-Reza
Canu, Stéphane Fischer, Asja Guns, Tias Kralj Novak, Petra Tsoumakas, Grigorios |
| Herausgeber: | Massih-Reza Amini/Stéphane Canu/Asja Fischer et al |
| Auflage: | 1st edition 2023 |
| Hersteller: |
Springer
Springer International Publishing AG Lecture Notes in Computer Science |
| Verantwortliche Person für die EU: | Springer Verlag GmbH, Tiergartenstr. 17, D-69121 Heidelberg, juergen.hartmann@springer.com |
| Maße: | 235 x 155 x 37 mm |
| Von/Mit: | Massih-Reza Amini (u. a.) |
| Erscheinungsdatum: | 19.03.2023 |
| Gewicht: | 1,025 kg |
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