Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Adversarial Attacks, Regression, and Numerical Stability Regularization   Adversarial attacks against neural networks in a regression setting are a
critical yet understudied problem. In this work, we advance the state of the
art by investigating adversarial attacks against regression networks and by
formulating a more effective defense against these attacks. In particular, we
take the perspective that adversarial attacks are likely caused by numerical
instability in learned functions. We introduce a stability inducing,
regularization based defense against adversarial attacks in the regression
setting. Our new and easy to implement defense is shown to outperform prior
approaches and to improve the numerical stability of learned functions.

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The categories of this paper are: astro-ph
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The categories of this paper are: plasm-ph
28
The categories of this paper are: alg-geom
17
The categories of this paper are: q-fin
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The categories of this paper are: supr-con
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The categories of this paper are: hep-th
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The categories of this paper are: hep-lat
31
The categories of this paper are: ao-sci
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The categories of this paper are: hep-ex
34
The categories of this paper are: chem-ph
25
The categories of this paper are: patt-sol
20
The categories of this paper are: acc-phys
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The categories of this paper are: econ
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The categories of this paper are: nucl-th
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The categories of this paper are: eess
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The categories of this paper are: math