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arXiv · 1707.04849

Minimax deviation strategies for machine learning and recognition with short learning samples

Michail Schlesinger·Evgeniy Vodolazskiy
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Abstract

The article is devoted to the problem of small learning samples in machine learning. The flaws of maximum likelihood learning and minimax learning are looked into and the concept of minimax deviation learning is introduced that is free of those flaws.

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Michail Schlesinger, Evgeniy Vodolazskiy. 2017-07-16. Minimax deviation strategies for machine learning and recognition with short learning samples. https://arxiv.org/abs/1707.04849

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