Titlebook: Web Intelligence: Research and Development; First Asia-Pacific C Ning Zhong,Yiju Yao,Setsuo Ohsuga Conference proceedings 2001 Springer-Ver

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书目名称Web Intelligence: Research and Development网络公开度学科排名




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书目名称Web Intelligence: Research and Development被引频次学科排名




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Nick Cerconeeral others. We, the present authors, have thus merely compiled and explained the works of others (with the exception of a few minor contributions of our own). Let us mention the origin of this treatise. A couple of years ago, J. Peetre suggested to the second author, J. Lofstrom, writing a book on

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W. Lewis Johnsonition satisfy the extremal condition . (ξ) . (ξ) ≤ ., (7.0.1) where . is a non-negative matrix. By means of a reformulation we reduce the corresponding interpolation problem to a degenerate one. This degenerate problem has a unique solution which can be found with the help of the results of Chapter

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W. Lewis Johnson exceptional if it is rational inner one. A . is a sequence .={γ.}0≤<∞ of complex numbers satisfying the condition |γ.| < 1 for every .. The Schur algorithm establishes a one-to-one correspondence between the set Ω of all contractive sequences .={γ.}0≤<∞ and the set of all non-exceptional Schur func

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Riichiro Mizoguchin problems, methods and applications. The authors decided to start working on this book during the regional CBMS conference in Lincoln, Nebraska organized by F. Gilfeather and D. Larson. The principal lecturer, J. William Helton, presented ten lectures on operator and systems theory and the interpla

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Jose Aguilar,Ernst Leissifying neurodegenerative diseases. For this purpose accurate prediction is important but the localisation of the areas that play a significant role in the prediction is also crucial, in order to gain clinicians’ trust and reassurance about the performance of a prediction model. Most interpretability

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Jose Aguilar,Ernst Leissng with the acknowledged ability of neural-network methods to analyse image data, would suggest that accurate models for lesions can now be constructed by a deep neural network. However an important difficulty arises from the lack of annotated images from various parts of the body. Our proposed appr