Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Distributed Training Algorithm of Generative Adversarial Networks with
  Quantized Gradients   Training generative adversarial networks (GAN) in a distributed fashion is a
promising technology since it is contributed to training GAN on a massive of
data efficiently in real-world applications. However, GAN is known to be
difficult to train by SGD-type methods (may fail to converge) and the
distributed SGD-type methods may also suffer from massive amount of
communication cost. In this paper, we propose a {distributed GANs training
algorithm with quantized gradient, dubbed DQGAN,} which is the first
distributed training method with quantized gradient for GANs. The new method
trains GANs based on a specific single machine algorithm called Optimistic
Mirror Descent (OMD) algorithm, and is applicable to any gradient compression
method that satisfies a general $\delta$-approximate compressor. The
error-feedback operation we designed is used to compensate for the bias caused
by the compression, and moreover, ensure the convergence of the new method.
Theoretically, we establish the non-asymptotic convergence of {DQGAN} algorithm
to first-order stationary point, which shows that the proposed algorithm can
achieve a linear speedup in the parameter server model. Empirically, our
experiments show that our {DQGAN} algorithm can reduce the communication cost
and save the training time with slight performance degradation on both
synthetic and real datasets.

17
The categories of this paper are: q-fin
30
The categories of this paper are: q-alg
29
The categories of this paper are: funct-an
22
The categories of this paper are: chao-dyn
4
The categories of this paper are: cond-mat
11
The categories of this paper are: hep-lat
32
The categories of this paper are: atom-ph
25
The categories of this paper are: patt-sol
23
The categories of this paper are: solv-int
35
The categories of this paper are: mtrl-th
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The categories of this paper are: adap-org
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The categories of this paper are: comp-gas
12
The categories of this paper are: nucl-th
5
The categories of this paper are: gr-qc
3
The categories of this paper are: physics
7
The categories of this paper are: hep-th