Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Characterization of the convergence of stationary Fokker-Planck learning   The convergence properties of the stationary Fokker-Planck algorithm for the
estimation of the asymptotic density of stochastic search processes is studied.
Theoretical and empirical arguments for the characterization of convergence of
the estimation in the case of separable and nonseparable nonlinear optimization
problems are given. Some implications of the convergence of stationary
Fokker-Planck learning for the inference of parameters in artificial neural
network models are outlined.

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The categories of this paper are: supr-con
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The categories of this paper are: math
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The categories of this paper are: eess
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The categories of this paper are: q-fin
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The categories of this paper are: mtrl-th
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The categories of this paper are: funct-an
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The categories of this paper are: acc-phys
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The categories of this paper are: plasm-ph
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The categories of this paper are: cmp-lg
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The categories of this paper are: hep-ph
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The categories of this paper are: ao-sci
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The categories of this paper are: comp-gas
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The categories of this paper are: econ
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The categories of this paper are: hep-lat
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The categories of this paper are: math-ph
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The categories of this paper are: quant-ph