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Parallel machine learning on big data

Published:01 September 2012Publication History
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Abstract

On algorithms for parallel machine learning, and why they need to be more efficient.

References

  1. Bekkerman, R., Bilenko, M., and Langford, J., Scaling up Machine Learning: Parallel and Distributed Approaches. Cambridge University Press, Cambridge, UK, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Scaling up Machine Learning, The Tutorial. http://hunch.net/~large_scale_survey/Google ScholarGoogle Scholar
  3. Vowpal Rabbit (Fast Learning). http://hunch.net/~vwGoogle ScholarGoogle Scholar
  4. Agarwal, A., Chapelle, O., Dudik, M., and Langford, J., 2012. A Reliable Effective Terascale Linear Learning System. Available at: http://arxiv.org/abs/1110.4198Google ScholarGoogle Scholar

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  1. Parallel machine learning on big data

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            • Published in

              cover image XRDS: Crossroads, The ACM Magazine for Students
              XRDS: Crossroads, The ACM Magazine for Students  Volume 19, Issue 1
              Big Data
              Fall 2012
              75 pages
              ISSN:1528-4972
              EISSN:1528-4980
              DOI:10.1145/2331042
              Issue’s Table of Contents

              Copyright © 2012 ACM

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              Association for Computing Machinery

              New York, NY, United States

              Publication History

              • Published: 1 September 2012

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