Titlebook: Scleroderma; From Pathogenesis to John Varga,Christopher P. Denton,Fredrick M. Wigle Book 20121st edition Springer Science+Business Media,

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978-1-4614-9027-2Springer Science+Business Media, LLC 2012

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Yannick Allanore MD, PhD,Filemon K. Tan MD, PhDvel procedure for instance selection based on ., a generalization of traditional database tuples. This procedure has two tasks: building a model and selecting instances based on the model. For the first task, we propose to merge data tuples while ensuring some criteria are satisfied. This merge oper

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Robyn T. Domsic MD, MPH,Thomas A. Medsger Jr. MDvel procedure for instance selection based on ., a generalization of traditional database tuples. This procedure has two tasks: building a model and selecting instances based on the model. For the first task, we propose to merge data tuples while ensuring some criteria are satisfied. This merge oper

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Lorinda Chung MD, MS,Jaap Fransen MD,Frank H. J. Van den Hoogen MD, PhDovery and data mining (KDD) is growingrapidly as an emerging field. However, no matter how powerfulcomputers are now or will be in the future, KDD researchers andpractitioners must consider how to manage ever-growing data which is,ironically, due to the extensive use of computers and ease of datacol

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vel procedure for instance selection based on ., a generalization of traditional database tuples. This procedure has two tasks: building a model and selecting instances based on the model. For the first task, we propose to merge data tuples while ensuring some criteria are satisfied. This merge oper

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Francesco Zulian MDvious tuning and instance-specific regression, while mitigating their weaknesses. Specifically, ISAC combines the two techniques to create a portfolio where each solver is tuned to tackle a specific type of problem instance in the training set. This is achieved using the assumption that problem inst

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Ivan Foeldvari MDvious tuning and instance-specific regression, while mitigating their weaknesses. Specifically, ISAC combines the two techniques to create a portfolio where each solver is tuned to tackle a specific type of problem instance in the training set. This is achieved using the assumption that problem inst