9789819557943 - graph neural network training: from data management perspective (machine learning: foundations, methodologies, and applications) (13 resultados)

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Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail
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Hardcover. Condición: new. Hardcover. Graph Neural Networks (GNNs) have revolutionized the way we learn representations from graph-structured data, becoming a cornerstone for applications in social networks, recommendation systems, biology, and beyond. However, mainstream GNNs rely heavily on message passing, an iterative proces…s of propagating information between connected nodes. While powerful, this method often incurs significant computational costs, making efficient training a growing challenge as graph sizes scale up.This book addresses these challenges by offering a comprehensive exploration of efficient GNN training through the lens of data management. It highlights how innovative techniques, rooted in decades of graph processing research, can optimize the entire training process without compromising performance. By focusing on system-level enhancements and practical solutions, it provides actionable strategies to overcome efficiency bottlenecks in large-scale GNN training.Readers will gain a deeper understanding of the graph data lifecycle in GNN training, with examples that demonstrate how data management techniques can significantly enhance scalability and performance. The book is designed for a broad audience, including students, researchers, and professionals, offering clear explanations and practical insights for anyone looking to master efficient GNN training. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books
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EUR 150,29
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Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
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Hardcover. Condición: Brand New. 203 pages. 6.14x0.50x9.21 inches. In Stock.

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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Graph Neural Networks (GNNs) have revolutionized the way we learn representations from graph-structured data, becoming a cornerstone for applications in social networks, recommendation systems, biology, and beyond. However, mainstream GNNs rely heavily on… message passing, an iterative process of propagating information between connected nodes. While powerful, this method often incurs significant computational costs, making efficient training a growing challenge as graph sizes scale up.This book addresses these challenges by offering a comprehensive exploration of efficient GNN training through the lens of data management. It highlights how innovative techniques, rooted in decades of graph processing research, can optimize the entire training process without compromising performance. By focusing on system-level enhancements and practical solutions, it provides actionable strategies to overcome efficiency bottlenecks in large-scale GNN training.Readers will gain a deeper understanding of the graph data lifecycle in GNN training, with examples that demonstrate how data management techniques can significantly enhance scalability and performance. The book is designed for a broad audience, including students, researchers, and professionals, offering clear explanations and practical insights for anyone looking to master efficient GNN training.

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Librería: Books Puddle, New York, NY, Estados Unidos de AmericaBooks Puddle
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EUR 214,38
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.
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EUR 139,09
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Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Graph Neural Networks (GNNs) have revolutionized the way we learn representations from graph-structured data, becoming a cornerstone for applications in social networks, recommendation systems, biology, and beyond. However, mainstream GNNs… rely heavily on message passing, an iterative process of propagating information between connected nodes. While powerful, this method often incurs significant computational costs, making efficient training a growing challenge as graph sizes scale up.This book addresses these challenges by offering a comprehensive exploration of efficient GNN training through the lens of data management. It highlights how innovative techniques, rooted in decades of graph processing research, can optimize the entire training process without compromising performance. By focusing on system-level enhancements and practical solutions, it provides actionable strategies to overcome efficiency bottlenecks in large-scale GNN training.Readers will gain a deeper understanding of the graph data lifecycle in GNN training, with examples that demonstrate how data management techniques can significantly enhance scalability and performance. The book is designed for a broad audience, including students, researchers, and professionals, offering clear explanations and practical insights for anyone looking to master efficient GNN training. 206 pp. Englisch.

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Librería: moluna, Greven, Alemaniamoluna
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt.

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Librería: CitiRetail, Stevenage, Reino UnidoCitiRetail
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EUR 152,82
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Hardcover. Condición: new. Hardcover. Graph Neural Networks (GNNs) have revolutionized the way we learn representations from graph-structured data, becoming a cornerstone for applications in social networks, recommendation systems, biology, and beyond. However, mainstream GNNs rely heavily on message passing, an iterative proces…s of propagating information between connected nodes. While powerful, this method often incurs significant computational costs, making efficient training a growing challenge as graph sizes scale up.This book addresses these challenges by offering a comprehensive exploration of efficient GNN training through the lens of data management. It highlights how innovative techniques, rooted in decades of graph processing research, can optimize the entire training process without compromising performance. By focusing on system-level enhancements and practical solutions, it provides actionable strategies to overcome efficiency bottlenecks in large-scale GNN training.Readers will gain a deeper understanding of the graph data lifecycle in GNN training, with examples that demonstrate how data management techniques can significantly enhance scalability and performance. The book is designed for a broad audience, including students, researchers, and professionals, offering clear explanations and practical insights for anyone looking to master efficient GNN training. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

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Librería: preigu, Osnabrück, Alemaniapreigu
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EUR 123,00
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Buch. Condición: Neu. Graph Neural Network Training | From Data Management Perspective | Yanyan Shen (u. a.) | Buch | Machine Learning: Foundations, Methodologies, and Applications | vii | Englisch | 2026 | Springer | EAN 9789819557943 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg…, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.

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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000
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EUR 139,09
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Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Graph Neural Networks (GNNs) have revolutionized the way we learn representations from graph-structured data, becoming a cornerstone for applications in social networks, recommendation systems, biology, and beyond. However, mainstream GNNs rel…y heavily on message passing, an iterative process of propagating information between connected nodes. While powerful, this method often incurs significant computational costs, making efficient training a growing challenge as graph sizes scale up.This book addresses these challenges by offering a comprehensive exploration of efficient GNN training through the lens of data management. It highlights how innovative techniques, rooted in decades of graph processing research, can optimize the entire training process without compromising performance. By focusing on system-level enhancements and practical solutions, it provides actionable strategies to overcome efficiency bottlenecks in large-scale GNN training.Readers will gain a deeper understanding of the graph data lifecycle in GNN training, with examples that demonstrate how data management techniques can significantly enhance scalability and performance. The book is designed for a broad audience, including students, researchers, and professionals, offering clear explanations and practical insights for anyone looking to master efficient GNN training.Springer Nature Customer Service Center GmbH, Europaplatz 3,69115 Heidelberg, Germany, Heidelberg 206 pp. Englisch.

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Librería: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
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EUR 193,80
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Hardcover. Condición: new. Hardcover. Graph Neural Networks (GNNs) have revolutionized the way we learn representations from graph-structured data, becoming a cornerstone for applications in social networks, recommendation systems, biology, and beyond. However, mainstream GNNs rely heavily on message passing, an iterative proces…s of propagating information between connected nodes. While powerful, this method often incurs significant computational costs, making efficient training a growing challenge as graph sizes scale up.This book addresses these challenges by offering a comprehensive exploration of efficient GNN training through the lens of data management. It highlights how innovative techniques, rooted in decades of graph processing research, can optimize the entire training process without compromising performance. By focusing on system-level enhancements and practical solutions, it provides actionable strategies to overcome efficiency bottlenecks in large-scale GNN training.Readers will gain a deeper understanding of the graph data lifecycle in GNN training, with examples that demonstrate how data management techniques can significantly enhance scalability and performance. The book is designed for a broad audience, including students, researchers, and professionals, offering clear explanations and practical insights for anyone looking to master efficient GNN training. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

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Librería: Majestic Books, Hounslow, Reino UnidoMajestic Books
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EUR 226,16
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Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios
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EUR 225,28
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Condición: New. PRINT ON DEMAND.