Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Bayesian high-dimensional linear regression with generic spike-and-slab
  priors   Spike-and-slab priors are popular Bayesian solutions for high-dimensional
linear regression problems. Previous theoretical studies on spike-and-slab
methods focus on specific prior formulations and use prior-dependent conditions
and analyses, and thus can not be generalized directly. In this paper, we
propose a class of generic spike-and-slab priors and develop a unified
framework to rigorously assess their theoretical properties. Technically, we
provide general conditions under which generic spike-and-slab priors can
achieve the nearly-optimal posterior contraction rate and the model selection
consistency. Our results include those of Narisetty and He (2014) and Castillo
et al. (2015) as special cases.

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The categories of this paper are: math-ph
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The categories of this paper are: quant-ph
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The categories of this paper are: hep-ex
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The categories of this paper are: q-bio
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The categories of this paper are: hep-th
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The categories of this paper are: q-alg
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The categories of this paper are: gr-qc
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The categories of this paper are: comp-gas
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The categories of this paper are: supr-con
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The categories of this paper are: acc-phys
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The categories of this paper are: q-fin
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The categories of this paper are: plasm-ph
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The categories of this paper are: chao-dyn
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The categories of this paper are: bayes-an
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The categories of this paper are: solv-int
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The categories of this paper are: adap-org