Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Subspace Attack: Exploiting Promising Subspaces for Query-Efficient
  Black-box Attacks   Unlike the white-box counterparts that are widely studied and readily
accessible, adversarial examples in black-box settings are generally more
Herculean on account of the difficulty of estimating gradients. Many methods
achieve the task by issuing numerous queries to target classification systems,
which makes the whole procedure costly and suspicious to the systems. In this
paper, we aim at reducing the query complexity of black-box attacks in this
category. We propose to exploit gradients of a few reference models which
arguably span some promising search subspaces. Experimental results show that,
in comparison with the state-of-the-arts, our method can gain up to 2x and 4x
reductions in the requisite mean and medium numbers of queries with much lower
failure rates even if the reference models are trained on a small and
inadequate dataset disjoint to the one for training the victim model. Code and
models for reproducing our results will be made publicly available.

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The categories of this paper are: q-alg
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The categories of this paper are: math-ph
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The categories of this paper are: nucl-th
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The categories of this paper are: chem-ph
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The categories of this paper are: hep-th
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The categories of this paper are: solv-int
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The categories of this paper are: alg-geom
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The categories of this paper are: plasm-ph
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The categories of this paper are: dg-ga
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The categories of this paper are: bayes-an
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The categories of this paper are: comp-gas
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The categories of this paper are: ao-sci
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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: nlin
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The categories of this paper are: quant-ph