Core Concepts
Auto-Train-Once (ATO) introduces an innovative network pruning algorithm designed to automatically reduce the computational and storage costs of DNNs.
Stats
"Our method achieves 72.02% Top-1 accuracy and 90.19% Top-5 accuracy while the results of other counterparts are below the baseline results."
"Under pruned FLOPs of 30%, our algorithm archives the best Top-1 acc compared with other methods."
Quotes
"Our solution, Auto-Train-Once (ATO), introduces an innovative network pruning algorithm designed to automatically reduce the computational and storage costs of DNNs."
"During the model training phase, a controller network dynamically generates the binary mask to guide the pruning of the target model."