Deep neural network compression : from sufficient to scarce data
The success of overparameterized deep neural networks (DNNs) poses a great challenge to deploy computationally expensive models on edge devices. Numerous model compression (pruning, quantization) methods have been proposed to overcome this challenge: Pruning eliminates unimportant parameters, while...
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Format: | Thesis-Doctor of Philosophy |
Language: | English |
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Nanyang Technological University
2021
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Online Access: | https://hdl.handle.net/10356/146245 |
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Institution: | Nanyang Technological University |
Language: | English |