Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: High-Capacity Expert Binary Networks   Network binarization is a promising hardware-aware direction for creating
efficient deep models. Despite its memory and computational advantages,
reducing the accuracy gap between binary models and their real-valued
counterparts remains an unsolved challenging research problem. To this end, we
make the following 3 contributions: (a) To increase model capacity, we propose
Expert Binary Convolution, which, for the first time, tailors conditional
computing to binary networks by learning to select one data-specific expert
binary filter at a time conditioned on input features. (b) To increase
representation capacity, we propose to address the inherent information
bottleneck in binary networks by introducing an efficient width expansion
mechanism which keeps the binary operations within the same budget. (c) To
improve network design, we propose a principled binary network growth mechanism
that unveils a set of network topologies of favorable properties. Overall, our
method improves upon prior work, with no increase in computational cost, by
$\sim6 \%$, reaching a groundbreaking $\sim 71\%$ on ImageNet classification.
Code will be made available
$\href{https://www.adrianbulat.com/binary-networks}{here}$.

35
The categories of this paper are: mtrl-th
29
The categories of this paper are: funct-an
20
The categories of this paper are: acc-phys
4
The categories of this paper are: cond-mat
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The categories of this paper are: atom-ph
6
The categories of this paper are: astro-ph
18
The categories of this paper are: econ
34
The categories of this paper are: chem-ph
33
The categories of this paper are: plasm-ph
0
The categories of this paper are: hep-ph
17
The categories of this paper are: q-fin
14
The categories of this paper are: math-ph
7
The categories of this paper are: hep-th
3
The categories of this paper are: physics
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The categories of this paper are: alg-geom
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The categories of this paper are: gr-qc