Making Models Shallow Again: Jointly Learning to Reduce Non-Linearity and Depth for Latency-Efficient Private Inference

Author:

Kundu Souvik1,Zhang Yuke2,Chen Dake2,Beerel Peter A.2

Affiliation:

1. Intel Labs,San Diego,USA

2. University of Southern California,Los Angeles,USA

Publisher

IEEE

Reference24 articles.

1. DNR

2. Be Your Own Teacher: Improve the Performance of Convolutional Neural Networks via Self Distillation

3. and Peter A Beerel. Learning to linearize deep neural networks for secure and efficient private inference;kundu;ICLRE,2023

4. Wide residual networks;zagoruyko,2016

5. AttentionLite: Towards Efficient Self-Attention Models for Vision

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