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Square Attack: a query-efficient black-box adversarial attack via random search

Nicolas Henri Bernard Flammarion, Maksym Andriushchenko, Francesco Croce

We propose the Square Attack, a new score-based black-box

l_2

and

l_\infty

adversarial attack that does not rely on local gradient information and thus is not affected by gradient masking. The Square Attack is based on a randomized search scheme where ...

2020

Recherche locale (optimisation)

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Chattez avec Graph Search

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Square Attack: a query-efficient black-box adversarial attack via random search

Safe non-smooth black-box optimization with application to policy search

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On the Almost Sure Convergence of Stochastic Gradient Descent in Non-Convex Problems

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Extrapolation for Large-batch Training in Deep Learning

Combinatorial optimization of Dedicated Bus Lane layout in urban networks with dynamic congestion

A Computational Method for Identifying the Optimum Buffer Size in the Era of Zero Defect Manufacturing

A new wake model and comparison of eight algorithms for layout optimization of wind farms in complex terrain

Extrapolation for Large-batch Training in Deep Learning

Safe non-smooth black-box optimization with application to policy search

Design of structures that adapt to loads through large shape changes

Optimal target assignment for massive spectroscopic surveys

On the Almost Sure Convergence of Stochastic Gradient Descent in Non-Convex Problems

Assisted Specification of Discrete Choice Models

Square Attack: a query-efficient black-box adversarial attack via random search