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Keyword: second-order information ×Clear all

2 claims from 1 paper

1. Computer Science › Advanced Neural Network Applications

   Filter Sketch for Network Pruning

   Lin, Cao, Li et al. · IEEE Transactions on Neural Networks and Learning Systems · 2021

   The paper presents FilterSketch, a pruning method that treats preserving pre-trained filter information as a matrix sketch problem and reports large FLOPs and parameter reductions with small accuracy loss.

   Unchecked2 claims
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   1. UncheckedFilterSketch prunes networks without training from scratch or iterative data-driven optimisation, cutting the time cost of pruning optimisation by orders of magnitude.“FilterSketch requires neither training from scratch nor data-driven iterative optimization, leading to a several-orders-of-magnitude reduction of time cost in the optimization of pruning.”
   2. UncheckedOn ILSVRC-2012, FilterSketch cuts 45.5% of FLOPs and 43.0% of parameters in ResNet-50, with a 0.69% accuracy drop.“On ILSVRC-2012, it reduces 45.5% of FLOPs and removes 43.0% of parameters with only 0.69% accuracy drop for ResNet-50.”