English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Open

Budgeted pruning is the problem of pruning under resource constraints. Inbudgeted pruning, how to distribute the resources across layers (i.e., sparsityallocation) is the key problem. Traditional methods solve it by discretelysearching for the layer-wise pruning ratios, which lacks efficiency. In thispaper, we propose Differentiable Sparsity Allocation (DSA), an efficientend-to-end budgeted pruning flow. Utilizing a novel differentiable pruningprocess, DSA finds the layer-wise pruning ratios with gradient-basedoptimization. It allocates sparsity in continuous space, which is moreefficient than methods based on discrete evaluation and search. Furthermore,DSA could work in a pruning-from-scratch manner, whereas traditional budgetedpruning methods are applied to pre-trained models. Experimental results onCIFAR-10 and ImageNet show that DSA could achieve superior performance thancurrent iterative budgeted pruning methods, and shorten the time cost of theoverall pruning process by at least 1.5x in the meantime.

DSA: More Efficient Budgeted Pruning via Differentiable Sparsity Allocation