# Leveraging Filter Correlations for Deep Model Compression

@article{Singh2020LeveragingFC,
title={Leveraging Filter Correlations for Deep Model Compression},
author={Pravendra Singh and Vinay Kumar Verma and Piyush Rai and Vinay P. Namboodiri},
journal={2020 IEEE Winter Conference on Applications of Computer Vision (WACV)},
year={2020},
pages={824-833}
}
• Pravendra Singh, +1 author Vinay P. Namboodiri
• Published 26 November 2018
• Computer Science, Engineering, Mathematics
• 2020 IEEE Winter Conference on Applications of Computer Vision (WACV)
We present a filter correlation based model compression approach for deep convolutional neural networks. Our approach iteratively identifies pairs of filters with the largest pairwise correlations and drops one of the filters from each such pair. However, instead of discarding one of the filters from each such pair naïvely, the model is re-optimized to make the filters in these pairs maximally correlated, so that discarding one of the filters from the pair results in minimal information loss…

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