Titlebook: Machine Learning: ECML 2004; 15th European Confer Jean-François Boulicaut,Floriana Esposito,Dino Ped Conference proceedings 2004 Springer-V

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Pedro Domingosow covers only linear transformations while the treat­ ment of matrices has been delegated to a new chapter, chapter 111. The discussion of dual spaces has been978-3-662-01545-2Series ISSN 0072-7830 Series E-ISSN 2196-9701

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David J. Handow covers only linear transformations while the treat­ ment of matrices has been delegated to a new chapter, chapter 111. The discussion of dual spaces has been978-3-662-01545-2Series ISSN 0072-7830 Series E-ISSN 2196-9701

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Jean-François Boulicaut,Floriana Esposito,Dino PedIncludes supplementary material:

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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/m/image/620752.jpg

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Machine Learning: ECML 2004978-3-540-30115-8Series ISSN 0302-9743 Series E-ISSN 1611-3349

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Random Matrices in Data AnalysisWe show how carefully crafted random matrices can achieve distance-preserving dimensionality reduction, accelerate spectral computations, and reduce the sample complexity of certain kernel methods.