Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Robustness Guarantees for Deep Neural Networks on Videos   The widespread adoption of deep learning models places demands on their
robustness. In this paper, we consider the robustness of deep neural networks
on videos, which comprise both the spatial features of individual frames
extracted by a convolutional neural network and the temporal dynamics between
adjacent frames captured by a recurrent neural network. To measure robustness,
we study the maximum safe radius problem, which computes the minimum distance
from the optical flow sequence obtained from a given input to that of an
adversarial example in the neighbourhood of the input. We demonstrate that,
under the assumption of Lipschitz continuity, the problem can be approximated
using finite optimisation via discretising the optical flow space, and the
approximation has provable guarantees. We then show that the finite
optimisation problem can be solved by utilising a two-player turn-based game in
a cooperative setting, where the first player selects the optical flows and the
second player determines the dimensions to be manipulated in the chosen flow.
We employ an anytime approach to solve the game, in the sense of approximating
the value of the game by monotonically improving its upper and lower bounds. We
exploit a gradient-based search algorithm to compute the upper bounds, and the
admissible A* algorithm to update the lower bounds. Finally, we evaluate our
framework on the UCF101 video dataset.

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The categories of this paper are: physics
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The categories of this paper are: cond-mat
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The categories of this paper are: acc-phys
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The categories of this paper are: hep-lat
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The categories of this paper are: alg-geom
31
The categories of this paper are: ao-sci
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The categories of this paper are: quant-ph
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The categories of this paper are: funct-an
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The categories of this paper are: plasm-ph
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The categories of this paper are: atom-ph
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The categories of this paper are: q-fin
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The categories of this paper are: adap-org
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The categories of this paper are: nlin
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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: astro-ph