Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
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In den WarenkorbZustand: New. In.
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In den WarenkorbZustand: New.
Verlag: Springer International Publishing, Springer Nature Switzerland Feb 2022, 2022
ISBN 10: 3030974537 ISBN 13: 9783030974534
Sprache: Englisch
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
EUR 69,54
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In den WarenkorbTaschenbuch. Zustand: Neu. Neuware -This book constitutes the refereed conference proceedings of the 30th International Conference on Inductive Logic Programming, ILP 2021, held in October 2021. Due to COVID-19 pandemic the conference was held virtually.The 16 papers and 3 short papers presented were carefully reviewed and selected from 19 submissions. Inductive Logic Programming (ILP) is a subfield of machine learning, which originally relied on logic programming as a uniform representation language for expressing examples, background knowledge and hypotheses. Due to its strong representation formalism, based on first-order logic, ILP provides an excellent means for multi-relational learning and data mining, and more generally for learning from structured data.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 296 pp. Englisch.
Verlag: Springer International Publishing, 2022
ISBN 10: 3030974537 ISBN 13: 9783030974534
Sprache: Englisch
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
EUR 69,54
Währung umrechnenAnzahl: 1 verfügbar
In den WarenkorbTaschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the refereed conference proceedings of the 30th International Conference on Inductive Logic Programming, ILP 2021, held in October 2021. Due to COVID-19 pandemic the conference was held virtually. The 16 papers and 3 short papers presented were carefully reviewed and selected from 19 submissions. Inductive Logic Programming (ILP) is a subfield of machine learning, which originally relied on logic programming as a uniform representation language for expressing examples, background knowledge and hypotheses. Due to its strong representation formalism, based on first-order logic, ILP provides an excellent means for multi-relational learning and data mining, and more generally for learning from structured data.