Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Fast ConvNets Using Group-wise Brain Damage   We revisit the idea of brain damage, i.e. the pruning of the coefficients of
a neural network, and suggest how brain damage can be modified and used to
speedup convolutional layers. The approach uses the fact that many efficient
implementations reduce generalized convolutions to matrix multiplications. The
suggested brain damage process prunes the convolutional kernel tensor in a
group-wise fashion by adding group-sparsity regularization to the standard
training process. After such group-wise pruning, convolutions can be reduced to
multiplications of thinned dense matrices, which leads to speedup. In the
comparison on AlexNet, the method achieves very competitive performance.

31
The categories of this paper are: ao-sci
17
The categories of this paper are: q-fin
13
The categories of this paper are: quant-ph
29
The categories of this paper are: funct-an
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The categories of this paper are: chem-ph
32
The categories of this paper are: atom-ph
16
The categories of this paper are: stat
8
The categories of this paper are: hep-ex
30
The categories of this paper are: q-alg
19
The categories of this paper are: eess
28
The categories of this paper are: alg-geom
4
The categories of this paper are: cond-mat
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The categories of this paper are: math-ph
25
The categories of this paper are: patt-sol
9
The categories of this paper are: nlin
6
The categories of this paper are: astro-ph