Parsimonious Inference on Convolutional Neural Networks: Learning and applying on-line kernel activation rules

Abstract

A new, radical CNN design approach is presented in this paper, considering the reduction of the total computational load during inference. This is achieved by a new holistic intervention on both the CNN architecture and the training procedure, which targets to the parsimonious inference by learning to exploit or remove the redundant capacity of a CNN… (More)

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Cite this paper

@article{Theodorakopoulos2017ParsimoniousIO, title={Parsimonious Inference on Convolutional Neural Networks: Learning and applying on-line kernel activation rules}, author={Ilias Theodorakopoulos and V. Pothos and Dimitris Kastaniotis and Nikos Fragoulis}, journal={CoRR}, year={2017}, volume={abs/1701.05221} }