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review-article

Algorithmic and statistical challenges in modern largescale data analysis are the focus of MMDS 2008

Published: 20 December 2008 Publication History

Abstract

We provide a report for the ACM SIGKDD community about the 2008 Workshop on Algorithms for Modern Massive Data Sets (MMDS 2008), its origin in MMDS 2006, and future directions for this interdisciplinary research area.

Reference

[1]
G.H. Golub, M.W. Mahoney P. Drineas, and L.-H. Lim, "Bridging the gap between numerical linear algebra, theoretical computer science, and data applications," SIAM News, 39, no. 8, (2006).

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  1. Algorithmic and statistical challenges in modern largescale data analysis are the focus of MMDS 2008

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      cover image ACM SIGKDD Explorations Newsletter
      ACM SIGKDD Explorations Newsletter  Volume 10, Issue 2
      December 2008
      98 pages
      ISSN:1931-0145
      EISSN:1931-0153
      DOI:10.1145/1540276
      Issue’s Table of Contents

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 20 December 2008
      Published in SIGKDD Volume 10, Issue 2

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      • (2016)Challenges in large-graph processing: A vision2016 5th International Conference on Computer Science and Network Technology (ICCSNT)10.1109/ICCSNT.2016.8070124(84-88)Online publication date: Dec-2016
      • (2013)Improved Matrix Algorithms via the Subsampled Randomized Hadamard TransformSIAM Journal on Matrix Analysis and Applications10.1137/12087454034:3(1301-1340)Online publication date: Jan-2013
      • (2011)Computation in large-scale scientific and internet data applications is a focus of MMDS 2010ACM SIGKDD Explorations Newsletter10.1145/1964897.196491412:2(59-62)Online publication date: 31-Mar-2011
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