Sprache: Chinesisch
Verlag: Foreign Languages Press, 2011
ISBN 10: 7119054708 ISBN 13: 9787119054704
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Soft cover. Zustand: New. This dictionary can also be used as a textbook for learning Chinese characters. The dictionary includes the most common 1,700 Chinese characters which are fundamental for learning and using the Chinese language. Readers can quickly look up an unfamiliar character in the dictionary, without needing to know its pronunciation, radical or stroke number. This is the first dictionary to list radicals as an entry.
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In den WarenkorbHardcover. Zustand: new. Hardcover. The goal of this Special Issue is to promote hybrid data processing by combining machine learning with experts' input, data safety, and security. AI technology and machine learning technology are developing rapidly. Data contain important information that can advance human knowledge and enhance AI capabilities. Meanwhile, requirements for data mining and data processing are expanding. Machine learning and deep learning may achieve excellent results, but in some cases, a balance can be reached by involving experienced experts to save resources and improve outcomes. In mining and analyzing data, the issues of data safety, data security, and data privacy also need to be suitably considered. This Special Issue presents ten rigorously reviewed manuscripts that study how to integrate hybrid data intelligence with experts' input, expert systems, safety, and security through decentralized reputation systems, blockchain technology, linkable ring signatures, collaborative filtering, contrastive learning, graph neural networks, feature selection, sample imbalance, few-shot learning, contrastive learning, knowledge graphs, transfer learning, dynamic Gaussian Bayesian networks, the Manning formula, surface confluence, federated learning, trusted execution environments, optimal mechanisms, multi-attribute auctions, multi-scale loss, scenario reconfiguration, probabilistic models, topology reconfiguration models, etc., in scenarios of flood prediction, social recommendation, multi-auction, terrorist attack prediction, etc. We believe that these studies are valuable in this field. 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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Buch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The goal of this Special Issue is to promote hybrid data processing by combining machine learning with experts' input, data safety, and security. AI technology and machine learning technology are developing rapidly. Data contain important information that can advance human knowledge and enhance AI capabilities. Meanwhile, requirements for data mining and data processing are expanding. Machine learning and deep learning may achieve excellent results, but in some cases, a balance can be reached by involving experienced experts to save resources and improve outcomes. In mining and analyzing data, the issues of data safety, data security, and data privacy also need to be suitably considered. This Special Issue presents ten rigorously reviewed manuscripts that study how to integrate hybrid data intelligence with experts' input, expert systems, safety, and security through decentralized reputation systems, blockchain technology, linkable ring signatures, collaborative filtering, contrastive learning, graph neural networks, feature selection, sample imbalance, few-shot learning, contrastive learning, knowledge graphs, transfer learning, dynamic Gaussian Bayesian networks, the Manning formula, surface confluence, federated learning, trusted execution environments, optimal mechanisms, multi-attribute auctions, multi-scale loss, scenario reconfiguration, probabilistic models, topology reconfiguration models, etc., in scenarios of flood prediction, social recommendation, multi-auction, terrorist attack prediction, etc. We believe that these studies are valuable in this field.
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Buch. Zustand: Neu. Hybrid Data Processing by Combining Machine Learning, Expert, Safety and Security | Buch | Englisch | 2025 | MDPI AG | EAN 9783725835454 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.