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Does anyone have reference to a summary of run-time analyses for common machine learning algorithms (different flavors of NN, SVMs, etc)?

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Here are some superficial tables:

  • The Computational Mathematics of Statistical Data Mining. PPT

  • Table 1 in:

    Chu, C. T., Kim, S. K., Lin, Y. A., Yu, Y., Bradski, G. R., Ng, A. Y., & Olukotun, K. (2006). Mapreduce for machine learning on multicore. Neural Information Processing Systems (pp. 281–288). PDF

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    $\begingroup$ First link is dead. $\endgroup$ – fanbondi May 7 '19 at 8:52
  • $\begingroup$ Fixed broken link based on google search. However, there are multiple versions of the relevant presentation online, so this might not be an exact duplicate of the original one. $\endgroup$ – mkt - Reinstate Monica Sep 12 '19 at 12:53
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I wrote the following article: computational complexity of machine learning algorithms where I keep track of the (theoretical) complexity of learning algorithms and run time analysis based on log-log regressions.

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