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Machine Learning and Knowledge Discovery in Databases: Research Track: European Conference, ECML PKDD 2023, Turin, Italy, September 18–22, 2023, Proceedings, Part III: 14171 - Brossura
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The multi-volume set LNAI 14169 until 14175 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2023, which took place in Turin, Italy, in September 2023.
The 196 papers were selected from the 829 submissions for the Research Track, and 58 papers were selected from the 239 submissions for the Applied Data Science Track.
The volumes are organized in topical sections as follows:
Part I: Active Learning; Adversarial Machine Learning; Anomaly Detection; Applications; Bayesian Methods; Causality; Clustering.
Part II: Computer Vision; Deep Learning; Fairness; Federated Learning; Few-shot learning; Generative Models; Graph Contrastive Learning.
Part III: Graph Neural Networks; Graphs; Interpretability; Knowledge Graphs; Large-scale Learning.
Part IV: Natural Language Processing; Neuro/Symbolic Learning; Optimization; Recommender Systems; Reinforcement Learning; Representation Learning.
Part V: Robustness; Time Series; Transfer and Multitask Learning.
Part VI: Applied Machine Learning; Computational Social Sciences; Finance; Hardware and Systems; Healthcare & Bioinformatics; Human-Computer Interaction; Recommendation and Information Retrieval.
Part VII: Sustainability, Climate, and Environment.- Transportation & Urban Planning.- Demo.
Chapter 41 is available open access under a Creative Commons Attribution 4.0 International License via Springerlink.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
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Chapter 41 is available open access under a Creative Commons Attribution 4.0 International License via Springerlink.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
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Machine Learning and Knowledge Discovery in Databases: Research Track: European Conference, ECML PKDD 2023, Turin, Italy, September 18â"22, 2023, . (Lecture Notes in Artificial Intelligence)
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Machine Learning and Knowledge Discovery in Databases
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Machine Learning and Knowledge Discovery in Databases: Research Track
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The multi-volume set LNAI 14169 until 14175 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2023, which took place in Turin, Italy, in September 2023.The 196 papers were selected from the 829 submissions for the Research Track, and 58 papers were selected from the 239 submissions for the Applied Data Science Track.The volumes are organized in topical sections as follows:Part I:Active Learning;Adversarial Machine Learning;Anomaly Detection; Applications; Bayesian Methods; Causality; Clustering.Part II: Computer Vision; Deep Learning; Fairness; Federated Learning; Few-shot learning; Generative Models; Graph Contrastive Learning.Part III: Graph Neural Networks;Graphs; Interpretability;Knowledge Graphs; Large-scale Learning.Part IV: Natural Language Processing; Neuro/Symbolic Learning; Optimization; Recommender Systems; Reinforcement Learning;Representation Learning.Part V: Robustness; Time Series; Transfer and Multitask Learning.Part VI: Applied Machine Learning; Computational Social Sciences; Finance; Hardware and Systems; Healthcare & Bioinformatics; Human-Computer Interaction; Recommendation and Information Retrieval. Part VII:Sustainability, Climate, and Environment.-Transportation & Urban Planning.-Demo. 764 pp. Englisch. Codice articolo 9783031434174
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Machine Learning and Knowledge Discovery in Databases: Research Track : European Conference, ECML PKDD 2023, Turin, Italy, September 18¿22, 2023, Proceedings, Part III
Editore:
Springer Nature Switzerland, 2023
ISBN 10: 303143417X
ISBN 13: 9783031434174
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - The multi-volume set LNAI 14169 until 14175 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2023, which took place in Turin, Italy, in September 2023.The 196 papers were selected from the 829 submissions for the Research Track, and 58 papers were selected from the 239 submissions for the Applied Data Science Track.The volumes are organized in topical sections as follows:Part I:Active Learning;Adversarial Machine Learning;Anomaly Detection; Applications; Bayesian Methods; Causality; Clustering.Part II: Computer Vision; Deep Learning; Fairness; Federated Learning; Few-shot learning; Generative Models; Graph Contrastive Learning.Part III: Graph Neural Networks;Graphs; Interpretability;Knowledge Graphs; Large-scale Learning.Part IV: Natural Language Processing; Neuro/Symbolic Learning; Optimization; Recommender Systems; Reinforcement Learning;Representation Learning.Part V: Robustness; Time Series; Transfer and Multitask Learning.Part VI: Applied Machine Learning; Computational Social Sciences; Finance; Hardware and Systems; Healthcare & Bioinformatics; Human-Computer Interaction; Recommendation and Information Retrieval. Part VII:Sustainability, Climate, and Environment.-Transportation & Urban Planning.-Demo.Chapter 41 is available open access under a Creative Commons Attribution 4.0 International License via Springerlink. Codice articolo 9783031434174
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Machine Learning and Knowledge Discovery in Databases: Research Track
ISBN 10: 303143417X
ISBN 13: 9783031434174
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Taschenbuch. Condizione: Neu. Neuware -The multi-volume set LNAI 14169 until 14175 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2023, which took place in Turin, Italy, in September 2023.The 196 papers were selected from the 829 submissions for the Research Track, and 58 papers were selected from the 239 submissions for the Applied Data Science Track.The volumes are organized in topical sections as follows:Part I: Active Learning; Adversarial Machine Learning; Anomaly Detection; Applications; Bayesian Methods; Causality; Clustering.Part II: ¿Computer Vision; Deep Learning; Fairness; Federated Learning; Few-shot learning; Generative Models; Graph Contrastive Learning.Part III: ¿Graph Neural Networks; Graphs; Interpretability; Knowledge Graphs; Large-scale Learning.Part IV: ¿Natural Language Processing; Neuro/Symbolic Learning; Optimization; Recommender Systems; Reinforcement Learning; Representation Learning.Part V: ¿Robustness; Time Series; Transfer and Multitask Learning.Part VI: ¿Applied Machine Learning; Computational Social Sciences; Finance; Hardware and Systems; Healthcare & Bioinformatics; Human-Computer Interaction; Recommendation and Information Retrieval.¿Part VII: Sustainability, Climate, and Environment.- Transportation & Urban Planning.- Demo.Chapter 41 is available open access under a Creative Commons Attribution 4.0 International License via Springerlink.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 768 pp. Englisch. Codice articolo 9783031434174
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Machine Learning and Knowledge Discovery in Databa
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Machine Learning and Knowledge Discovery in Databa
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