Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Training Compact Neural Networks with Binary Weights and Low Precision
  Activations   In this paper, we propose to train a network with binary weights and
low-bitwidth activations, designed especially for mobile devices with limited
power consumption. Most previous works on quantizing CNNs uncritically assume
the same architecture, though with reduced precision. However, we take the view
that for best performance it is possible (and even likely) that a different
architecture may be better suited to dealing with low precision weights and
activations.
  Specifically, we propose a "network expansion" strategy in which we aggregate
a set of homogeneous low-precision branches to implicitly reconstruct the
full-precision intermediate feature maps. Moreover, we also propose a
group-wise feature approximation strategy which is very flexible and highly
accurate. Experiments on ImageNet classification tasks demonstrate the superior
performance of the proposed model, named Group-Net, over various popular
architectures. In particular, with binary weights and activations, we
outperform the previous best binary neural network in terms of accuracy as well
as saving more than 5 times computational complexity on ImageNet with ResNet-18
and ResNet-50.

31
The categories of this paper are: ao-sci
33
The categories of this paper are: plasm-ph
18
The categories of this paper are: econ
25
The categories of this paper are: patt-sol
16
The categories of this paper are: stat
30
The categories of this paper are: q-alg
6
The categories of this paper are: astro-ph
28
The categories of this paper are: alg-geom
37
The categories of this paper are: supr-con
27
The categories of this paper are: comp-gas
36
The categories of this paper are: cmp-lg
10
The categories of this paper are: q-bio
8
The categories of this paper are: hep-ex
5
The categories of this paper are: gr-qc
20
The categories of this paper are: acc-phys
0
The categories of this paper are: hep-ph