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Technical perspective: Compressing matrices for large-scale machine learning

Published: 24 April 2019 Publication History

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References

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Abadi, M. et al. Tensorflow: A system for large-scale machine learning. OSDI, 16 (2016), 265--283.
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Ewen, S., Tzoumas, K., Kaufmann, M. and Markl, V. Spinning fast iterative data flows. In Proceedings of VLDB Endow. 5, 11 (2012), 1268--1279.
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Ghoting, A. et al. SystemML: Declarative machine learning on MapReduce. ICDE. IEEE, 2011, 231--242.
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Low, Y. et al. GraphLab: A new parallel framework for machine learning. In Proceedings of the Conference on Uncertainty in Artificial Intelligence. (Catalina Island, CA, July 2010).
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Meng, X. et al. Mllib: Machine learning in Apache Spark. JMLR, 17, 1 (2016), 1235--1241.
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Paszke, A. et al. Automatic differentiation. PyTorch, 2017.
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Team, T.T.D. et al. Theano: A python framework for fast computation of mathematical expressions. arXiv preprint arXiv:1605.02688, 2016.
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Zaharia, M., Chodhury, M., Franklin, M.J., Shenker, A. and Stoica, I. Spark: Cluster computing with working sets. HotCloud 10, 2010.

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  • (2019)XOR-Based Boolean Matrix Decomposition2019 IEEE International Conference on Data Mining (ICDM)10.1109/ICDM.2019.00074(638-647)Online publication date: Nov-2019

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      cover image Communications of the ACM
      Communications of the ACM  Volume 62, Issue 5
      May 2019
      83 pages
      ISSN:0001-0782
      EISSN:1557-7317
      DOI:10.1145/3328504
      Issue’s Table of Contents
      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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      Publication History

      Published: 24 April 2019
      Published in CACM Volume 62, Issue 5

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      • (2019)XOR-Based Boolean Matrix Decomposition2019 IEEE International Conference on Data Mining (ICDM)10.1109/ICDM.2019.00074(638-647)Online publication date: Nov-2019

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