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Recently, Frankle & Carbin (2019) demonstrated that randomly-initialized dense networks contain subnetworks that once found can be trained to reach test accuracy comparable to the trained dense network.
Optimal brain damage
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Aojun Zhou, Anbang Yao, Yiwen Guo, Lin Xu, and Yurong Chen · 2017
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Adrian Bulat and Georgios Tzimiropoulos · 2019
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Jonathan Frankle and Michael Carbin · 2019
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Good subnetworks provably exist: Pruning via greedy forward selection
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Siman: Sign-to-magnitude network binarization
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