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arXiv · 1106.1216

Using More Data to Speed-up Training Time

Shai Shalev-Shwartz·Ohad Shamir·Eran Tromer
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Abstract

In many recent applications, data is plentiful. By now, we have a rather clear understanding of how more data can be used to improve the accuracy of learning algorithms. Recently, there has been a growing interest in understanding how more data can be leveraged to reduce the required training runtime. In this paper, we study the runtime of learning as a function of the number of available training examples, and underscore the main high-level techniques. We provide some initial positive results showing that the runtime can decrease exponentially while only requiring a polynomial growth of the number of examples, and spell-out several interesting open problems.

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Shai Shalev-Shwartz, Ohad Shamir, Eran Tromer. 2011-06-15. Using More Data to Speed-up Training Time. https://arxiv.org/abs/1106.1216

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