Model-Based Deep Learning: On the Intersection of Deep Learning and Optimization. (arXiv:2205.02640v1 [eess.SP])

Web: http://arxiv.org/abs/2205.02640

Decision making algorithms are used in a multitude of different applications.
Conventional approaches for designing decision algorithms employ principled and
simplified modelling, based on which one can determine decisions via tractable
optimization. More recently, deep learning approaches that use highly
parametric architectures tuned from data without relying on mathematical
models, are becoming increasingly popular. Model-based optimization and
data-centric deep learning are often considered to be distinct disciplines.
Here, we characterize them as edges of a continuous spectrum varying in
specificity …

arxiv deep deep learning learning model on optimization