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Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
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In den WarenkorbZustand: New. In.
Sprache: Englisch
Verlag: Springer, Berlin|Springer Nature Switzerland|Springer, 2023
ISBN 10: 3031434293 ISBN 13: 9783031434297
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Verlag: Springer-Nature New York Inc, 2023
ISBN 10: 3031434293 ISBN 13: 9783031434297
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Sprache: Englisch
Verlag: Springer, Berlin|Springer Nature Switzerland|Springer, 2023
ISBN 10: 3031434269 ISBN 13: 9783031434266
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Taschenbuch. Zustand: 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.
Taschenbuch. Zustand: Neu. Machine Learning and Knowledge Discovery in Databases: Applied Data Science and Demo Track | European Conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023, Proceedings, Part VII | Gianmarco de Francisci Morales (u. a.) | Taschenbuch | Lecture Notes in Computer Science | liv | Englisch | 2023 | Springer | EAN 9783031434297 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Zustand: Hervorragend. Zustand: Hervorragend | Seiten: 760 | Sprache: Englisch | Produktart: Bücher | 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.
Taschenbuch. Zustand: Neu. Machine Learning and Knowledge Discovery in Databases: Applied Data Science and Demo Track | European Conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023, Proceedings, Part VI | Gianmarco de Francisci Morales (u. a.) | Taschenbuch | Lecture Notes in Computer Science | lv | Englisch | 2023 | Springer | EAN 9783031434266 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 440 | Sprache: Englisch | Produktart: Bücher | 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.
Sprache: Englisch
Verlag: Springer-Nature New York Inc, 2023
ISBN 10: 3031434269 ISBN 13: 9783031434266
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
EUR 143,97
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In den WarenkorbPaperback. Zustand: Brand New. 758 pages. 9.25x6.10x1.51 inches. In Stock.
Sprache: Englisch
Verlag: Springer Nature Switzerland, 2023
ISBN 10: 3031434269 ISBN 13: 9783031434266
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: 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.
Zustand: Hervorragend. Zustand: Hervorragend | Seiten: 440 | Sprache: Englisch | Produktart: Bücher | 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.