3 citations · 4 across the 4 of their papers we have counts for
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cs.LG2022
Tiered Pruning for Efficient Differentialble Inference-Aware Neural Architecture Search
Sławomir Kierat, Mateusz Sieniawski, Denys Fridman +4
We propose three novel pruning techniques to improve the cost and results of inference-aware Differentiable Neural Architecture Search (DNAS). First, we introduce Prunode, a stocha…
cs.CV2022★ 3 cited
GPUNet: Searching the Deployable Convolution Neural Networks for GPUs
Linnan Wang, Chenhan Yu, Satish Salian +3
Customizing Convolution Neural Networks (CNN) for production use has been a challenging task for DL practitioners. This paper intends to expedite the model customization with a mod…