Components of Machine Learning: Binding Bits and FLOPS

Alexander Jung

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arXiv · 1910.12387

Components of Machine Learning: Binding Bits and FLOPS

Alexander Jung

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Abstract

Many machine learning problems and methods are combinations of three components: data, hypothesis space and loss function. Different machine learning methods are obtained as combinations of different choices for the representation of data, hypothesis space and loss function. After reviewing the mathematical structure of these three components, we discuss intrinsic trade-offs between statistical and computational properties of machine learning methods.

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Alexander Jung. 2019-10-25. Components of Machine Learning: Binding Bits and FLOPS. https://arxiv.org/abs/1910.12387

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