Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Convexly Constrained LiGME Model and Its Proximal Splitting Algorithm   For the sparsity-rank-aware least squares estimations, the LiGME (Linearly
involved Generalized Moreau Enhanced) model was established recently in [Abe,
Yamagishi, Yamada, 2020] to use certain nonconvex enhancements of linearly
involved convex regularizers without losing their overall convexities. In this
paper, for further advancement of the LiGME model by incorporating multiple a
priori knowledge as hard convex constraints, we newly propose a convexly
constrained LiGME (cLiGME) model. The cLiGME model can utilize multiple convex
constraints while preserving benefits achieved by the LiGME model. We also
present a proximal splitting type algorithm for the proposed cLiGME model.
Numerical experiments demonstrate the efficacy of the proposed model and the
proposed optimization algorithm in a scenario of signal processing application.

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The categories of this paper are: mtrl-th
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The categories of this paper are: solv-int
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The categories of this paper are: hep-th
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The categories of this paper are: patt-sol
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The categories of this paper are: q-fin
4
The categories of this paper are: cond-mat
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The categories of this paper are: comp-gas
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The categories of this paper are: adap-org
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The categories of this paper are: stat
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The categories of this paper are: cmp-lg
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The categories of this paper are: astro-ph
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The categories of this paper are: ao-sci
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The categories of this paper are: hep-ph
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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: gr-qc