Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Hybrid Pruning: Thinner Sparse Networks for Fast Inference on Edge
  Devices   We introduce hybrid pruning which combines both coarse-grained channel and
fine-grained weight pruning to reduce model size, computation and power demands
with no to little loss in accuracy for enabling modern networks deployment on
resource-constrained devices, such as always-on security cameras and drones.
Additionally, to effectively perform channel pruning, we propose a fast
sensitivity test that helps us quickly identify the sensitivity of within and
across layers of a network to the output accuracy for target multiplier
accumulators (MACs) or accuracy tolerance. Our experiment shows significantly
better results on ResNet50 on ImageNet compared to existing work, even with an
additional constraint of channels be hardware-friendly number.

31
The categories of this paper are: ao-sci
37
The categories of this paper are: supr-con
25
The categories of this paper are: patt-sol
2
The categories of this paper are: math
6
The categories of this paper are: astro-ph
16
The categories of this paper are: stat
12
The categories of this paper are: nucl-th
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The categories of this paper are: chao-dyn
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The categories of this paper are: eess
14
The categories of this paper are: math-ph
3
The categories of this paper are: physics
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The categories of this paper are: comp-gas
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The categories of this paper are: atom-ph
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The categories of this paper are: adap-org
5
The categories of this paper are: gr-qc
23
The categories of this paper are: solv-int