Deep Learning

Nicholas G. Polson; Vadim O. Sokolov

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arXiv · 1807.07987

Deep Learning

Nicholas G. Polson·Vadim O. Sokolov

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Abstract

Deep learning (DL) is a high dimensional data reduction technique for constructing high-dimensional predictors in input-output models. DL is a form of machine learning that uses hierarchical layers of latent features. In this article, we review the state-of-the-art of deep learning from a modeling and algorithmic perspective. We provide a list of successful areas of applications in Artificial Intelligence (AI), Image Processing, Robotics and Automation. Deep learning is predictive in its nature rather then inferential and can be viewed as a black-box methodology for high-dimensional function estimation.

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BibTeX RIS

Nicholas G. Polson, Vadim O. Sokolov. 2018-07-20. Deep Learning. https://arxiv.org/abs/1807.07987

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