Table 4 Different coefficient \(\alpha\) and weight combination threshold
From: A statistical approach for neural network pruning with application to internet of things
\(\alpha\) | 1e−5 | 5e−5 | |||||
|---|---|---|---|---|---|---|---|
T | 0.0001 | 0.001 | 0.01 | 0.0001 | 0.0005 | 0.001 | 0.005 |
Params (M) | 4.63 | 4,17 | 2.89 | 0.78 | 0.80 | 0.79 | 0.84 |
FLOPS (M) | 385.49 | 327.17 | 200.09 | 130.96 | 135.56 | 134.68 | 126.03 |
Accuracy (%) | 93.43 | 93.28 | 92.99 | 92.79 | 92.86 | 92.96 | 93.06 |