Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Forget the Learning Rate, Decay Loss   In the usual deep neural network optimization process, the learning rate is
the most important hyper parameter, which greatly affects the final convergence
effect. The purpose of learning rate is to control the stepsize and gradually
reduce the impact of noise on the network. In this paper, we will use a fixed
learning rate with method of decaying loss to control the magnitude of the
update. We used Image classification, Semantic segmentation, and GANs to verify
this method. Experiments show that the loss decay strategy can greatly improve
the performance of the model

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The categories of this paper are: chem-ph
20
The categories of this paper are: acc-phys
25
The categories of this paper are: patt-sol
18
The categories of this paper are: econ
33
The categories of this paper are: plasm-ph
22
The categories of this paper are: chao-dyn
7
The categories of this paper are: hep-th
3
The categories of this paper are: physics
4
The categories of this paper are: cond-mat
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The categories of this paper are: math-ph
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The categories of this paper are: astro-ph
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The categories of this paper are: q-fin
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The categories of this paper are: math
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The categories of this paper are: cmp-lg
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The categories of this paper are: q-bio
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The categories of this paper are: bayes-an