Deep Unfolding: Model-Based Inspiration of Novel Deep Architectures

@article{Hershey2014DeepUM,
  title={Deep Unfolding: Model-Based Inspiration of Novel Deep Architectures},
  author={John R. Hershey and Jonathan Le Roux and Felix Weninger},
  journal={CoRR},
  year={2014},
  volume={abs/1409.2574}
}
Model-based methods and deep neural networks have both been tremendously successful paradigms in machine learning. In model-based methods, we can easily express our problem domain knowledge in the constraints of the model at the expense of difficulties during inference. Deterministic deep neural networks are constructed in such a way that inference is straightforward, but we sacrifice the ability to easily incorporate problem domain knowledge. The goal of this paper is to provide a general… CONTINUE READING
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