PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
Anbieter: PBShop.store UK, Fairford, GLOS, Vereinigtes Königreich
EUR 59,52
Anzahl: 1 verfügbar
In den WarenkorbPAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
Sprache: Englisch
Verlag: Springer-Nature New York Inc, 2025
ISBN 10: 9819509874 ISBN 13: 9789819509874
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
EUR 90,57
Anzahl: 2 verfügbar
In den WarenkorbPaperback. Zustand: Brand New. 206 pages. 9.25x6.10x9.21 inches. In Stock.
Sprache: Englisch
Verlag: Springer-Verlag Gmbh Aug 2025, 2025
ISBN 10: 9819509874 ISBN 13: 9789819509874
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Taschenbuch. Zustand: Neu. Neuware -This book presents the proceedings from the Third International Workshop on Generalizing from Limited Resources in the Open World (GLOW) 2025 held in conjunction with the International Joint Conference on Artificial Intelligence, IJCAI 2025, in Montreal, Canada, during August 16-22, 2025.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 196 pp. Englisch.
Taschenbuch. Zustand: Neu. Generalizing from Limited Resources in the Open World | Third International Workshop, GLOW 2025, Held in Conjunction with IJCAI 2025, Montreal, Canada, August 16-22, 2025, Proceedings | Yuqing Ma (u. a.) | Taschenbuch | x | Englisch | 2025 | Springer | EAN 9789819509874 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Sprache: Englisch
Verlag: Springer, Springer Aug 2025, 2025
ISBN 10: 9819509874 ISBN 13: 9789819509874
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. Neuware - This book presents the proceedings from the Third International Workshop on Generalizing from Limited Resources in the Open World (GLOW) 2025 held in conjunction with the International Joint Conference on Artificial Intelligence, IJCAI 2025, in Montreal, Canada, during August 16-22, 2025.The 12 full papers in this book were carefully reviewed and selected from 27submissions. These papers focus on the academic exploration of efficient methodologies within the realm of artificial intelligence models. We concentrated on both data-efficient strategies, such as zero/few-shot learning and domain adaptation, as well as model-efficient approaches like model sparsification and compact model design.
Taschenbuch. Zustand: Neu. Generalizing from Limited Resources in the Open World | Second International Workshop, GLOW 2024, Held in Conjunction with IJCAI 2024, Jeju, South Korea, August 3, 2024, Proceedings | Jinyang Guo (u. a.) | Taschenbuch | x | Englisch | 2024 | Springer | EAN 9789819761241 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents the Proceedings from the Second International Workshop GLOW 2024 held in conjunction with the International Joint Conference on Artificial Intelligence, IJCAI 2024, in Jeju Island, South Korea, in August 2024.The 11 full papers and 4 short papers included in this book were carefully reviewed and selected from 22 submissions. They were organized in topical sections as follows: efficient methods for low-resource hardware; efficient fintuning with limited data; advancements in multimodal systems; recognition and reasoning in the open world.
Sprache: Englisch
Verlag: Springer, Springer Aug 2025, 2025
ISBN 10: 9819509874 ISBN 13: 9789819509874
Anbieter: Books-by-Floh, Paderborn, Deutschland
Taschenbuch. Zustand: Neu. Neuware -This book presents the proceedings from the Third International Workshop on Generalizing from Limited Resources in the Open World (GLOW) 2025 held in conjunction with the International Joint Conference on Artificial Intelligence, IJCAI 2025, in Montreal, Canada, during August 16-22, 2025.The 12 full papers in this book were carefully reviewed and selected from 27 submissions. These papers focus on the academic exploration of efficient methodologies within the realm of artificial intelligence models. We concentrated on both data-efficient strategies, such as zero/few-shot learning and domain adaptation, as well as model-efficient approaches like model sparsification and compact model design. 208 pp. Englisch.