Ge Precision Healthcare LLC

Attila Márk Rádics

Venkata Ratnam Saripalli

Junpyo Hong

Hans Krupakar

Rajesh Kumar Tamada

Guarav Kumar

Techniques are provided for compressing deep neural networks using a structured filter pruning method that is extensible and effective. According to an embodiment, a computer-implemented method comprises determining, by a system operatively coupled to a processor, importance scores for filters of layers of a neural network model previously trained until convergence for an inferencing task on a training dataset. The method further comprises removing, by the system, a subset of the filters from one or more layers of the layers based on the importance scores associated with the subset failing to satisfy a threshold importance score value. The method further comprises converting, by the system, the neural network model into a compressed neural network model with the subset of the filters removed.

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Nagykovácsi, Hungary

Attila Márk Rádics