Towards Network Simplification for Low-Cost Devices by Removing Synapses

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F18%3A43952603" target="_blank" >RIV/49777513:23520/18:43952603 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007/978-3-319-99579-3_7" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-319-99579-3_7</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-99579-3_7" target="_blank" >10.1007/978-3-319-99579-3_7</a>

Result language
angličtina
Original language name
Towards Network Simplification for Low-Cost Devices by Removing Synapses
Original language description
The deployment of robust neural network based models on low-cost devices touches the problem with hardware constraints like limited memory footprint and computing power. This work presents a general method for a rapid reduction of parameters (80–90%) in a trained (DNN or LSTM) network by removing its redundant synapses, while the classification accuracy is not significantly hurt. The massive reduction of parameters leads to a notable decrease of the model’s size and the actual prediction time of on-board classifiers. We show the pruning results on a simple speech recognition task, however, the method is applicable to any classification data.
Czech name
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Czech description
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Project
<a href="/en/project/LO1506" target="_blank" >LO1506: Sustainability support of the centre NTIS - New Technologies for the Information Society</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Speech and Computer 20th International Conference, SPECOM 2018 Leipzig, Germany, September 18–22, 2018, Proceedings
ISBN
978-3-319-99578-6
ISSN
0302-9743
e-ISSN
1611-3349
Number of pages
10
Pages from-to
58-67
Publisher name
Springer Nature Switzerland AG
Place of publication
Cham
Event location
Leipzig, Germany
Event date
Sep 18, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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