Deep Learning
This is an incremental review paper summarizing the state-of-the-art in deep learning for researchers and practitioners in related fields.
The paper reviews deep learning as a high-dimensional data reduction technique for constructing predictors in input-output models, highlighting its predictive nature and applications in AI, image processing, robotics, and automation.
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.