Articoli correlati a Scaling up Machine Learning: Parallel and Distributed...
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This integrated collection covers a range of parallelization platforms, concurrent programming frameworks and machine learning settings, with case studies.
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Informazioni sugli autori
Ron Bekkerman is a computer engineer and scientist whose experience spans across disciplines from video processing to business intelligence. Currently a senior research scientist at LinkedIn, he previously worked for a number of major companies including Hewlett-Packard and Motorola. Bekkerman's research interests lie primarily in the area of large-scale unsupervised learning. He is the corresponding author of several publications in top-tier venues, such as ICML, KDD, SIGIR, WWW, IJCAI, CVPR, EMNLP and JMLR.
Mikhail Bilenko is a researcher in the Machine Learning and Intelligence group at Microsoft Research. His research interests center on machine learning and data mining tasks that arise in the context of large behavioral and textual datasets. Bilenko's recent work has focused on learning algorithms that leverage user behavior to improve online advertising. His papers have been published at KDD, ICML, SIGIR, and WWW among other venues, and he has received best paper awards from SIGIR and KDD.
John Langford is a computer scientist working as a senior researcher at Yahoo! Research. Previously, he was affiliated with the Toyota Technological Institute and IBM T. J. Watson Research Center. Langford's work has been published at conferences and in journals including ICML, COLT, NIPS, UAI, KDD, JMLR and MLJ. He received the Pat Goldberg Memorial Best Paper Award, as well as best paper awards from ACM EC and WSDM. He is also the author of the popular machine learning weblog, hunch.net.
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Scaling Up Machine Learning: Parallel and Distributed Approaches
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Cambridge University Press, 2011
ISBN 10: 0521192242
ISBN 13: 9780521192248
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Scaling Up Machine Learning: Parallel and Distributed Approaches
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ISBN 13: 9780521192248
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Scaling up Machine Learning : Parallel and Distributed Approaches
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Cambridge University Press, 2011
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ISBN 13: 9780521192248
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Scaling Up Machine Learning Parallel and Distributed Approaches
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Cambridge University Press, 2011
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Scaling up Machine Learning: Parallel and Distributed Approaches
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Cambridge University Press, 2011
ISBN 10: 0521192242
ISBN 13: 9780521192248
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Scaling Up Machine Learning
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Gebunden. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. In many practical situations it is impossible to run existing machine learning methods on a single computer, because either the data is too large or the speed and throughput requirements are too demanding. Researchers and practitioners will find here a vari. Codice articolo 446929496
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