Fast Network Pruning and Feature Extraction by Using the Unit-OBS Algorithm
Abstract
The algorithm described in this article is based on the OBS algo(cid:173) rithm by Hassibi, Stork and Wolff ([1] and [2]). The main disad(cid:173) vantage of OBS is its high complexity. OBS needs to calculate the inverse Hessian to delete only one weight (thus needing much time to prune a big net) . A better algorithm should use this matrix to remove more than only one weight , because calculating the inverse Hessian takes the most time in the OBS algorithm. The algorithm, called Unit- OBS, described in this article is a method to overcome this disadvantage. This algorithm only needs to calculate the inverse Hessian once to remove one whole unit thus drastically reducing the time to prune big nets. A further advantage of Unit- OBS is that it can be used to do a feature extraction on the input data. This can be helpful on the understanding of unknown problems.
Cite
Text
Stahlberger and Riedmiller. "Fast Network Pruning and Feature Extraction by Using the Unit-OBS Algorithm." Neural Information Processing Systems, 1996.Markdown
[Stahlberger and Riedmiller. "Fast Network Pruning and Feature Extraction by Using the Unit-OBS Algorithm." Neural Information Processing Systems, 1996.](https://mlanthology.org/neurips/1996/stahlberger1996neurips-fast/)BibTeX
@inproceedings{stahlberger1996neurips-fast,
title = {{Fast Network Pruning and Feature Extraction by Using the Unit-OBS Algorithm}},
author = {Stahlberger, Achim and Riedmiller, Martin},
booktitle = {Neural Information Processing Systems},
year = {1996},
pages = {655-661},
url = {https://mlanthology.org/neurips/1996/stahlberger1996neurips-fast/}
}