Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: General Backpropagation Algorithm for Training Second-order Neural
  Networks   The artificial neural network is a popular framework in machine learning. To
empower individual neurons, we recently suggested that the current type of
neurons could be upgraded to 2nd order counterparts, in which the linear
operation between inputs to a neuron and the associated weights is replaced
with a nonlinear quadratic operation. A single 2nd order neurons already has a
strong nonlinear modeling ability, such as implementing basic fuzzy logic
operations. In this paper, we develop a general backpropagation (BP) algorithm
to train the network consisting of 2nd-order neurons. The numerical studies are
performed to verify of the generalized BP algorithm.

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The categories of this paper are: q-bio
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The categories of this paper are: funct-an
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The categories of this paper are: dg-ga
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The categories of this paper are: quant-ph
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The categories of this paper are: bayes-an
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The categories of this paper are: math-ph
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The categories of this paper are: patt-sol
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The categories of this paper are: adap-org
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The categories of this paper are: acc-phys
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The categories of this paper are: hep-ex
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The categories of this paper are: gr-qc
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The categories of this paper are: physics
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The categories of this paper are: econ
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The categories of this paper are: nucl-ex
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The categories of this paper are: comp-gas
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The categories of this paper are: chao-dyn