Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Going Grayscale: The Road to Understanding and Improving Unlearnable
  Examples   Recent work has shown that imperceptible perturbations can be applied to
craft unlearnable examples (ULEs), i.e. images whose content cannot be used to
improve a classifier during training. In this paper, we reveal the road that
researchers should follow for understanding ULEs and improving ULEs as they
were originally formulated (ULEOs). The paper makes four contributions. First,
we show that ULEOs exploit color and, consequently, their effects can be
mitigated by simple grayscale pre-filtering, without resorting to adversarial
training. Second, we propose an extension to ULEOs, which is called
ULEO-GrayAugs, that forces the generated ULEs away from channel-wise color
perturbations by making use of grayscale knowledge and data augmentations
during optimization. Third, we show that ULEOs generated using Multi-Layer
Perceptrons (MLPs) are effective in the case of complex Convolutional Neural
Network (CNN) classifiers, suggesting that CNNs suffer specific vulnerability
to ULEs. Fourth, we demonstrate that when a classifier is trained on ULEOs,
adversarial training will prevent a drop in accuracy measured both on clean
images and on adversarial images. Taken together, our contributions represent a
substantial advance in the state of art of unlearnable examples, but also
reveal important characteristics of their behavior that must be better
understood in order to achieve further improvements.

12
The categories of this paper are: nucl-th
23
The categories of this paper are: solv-int
8
The categories of this paper are: hep-ex
4
The categories of this paper are: cond-mat
26
The categories of this paper are: bayes-an
27
The categories of this paper are: comp-gas
25
The categories of this paper are: patt-sol
34
The categories of this paper are: chem-ph
3
The categories of this paper are: physics
14
The categories of this paper are: math-ph
33
The categories of this paper are: plasm-ph
0
The categories of this paper are: hep-ph
22
The categories of this paper are: chao-dyn
20
The categories of this paper are: acc-phys
21
The categories of this paper are: adap-org
32
The categories of this paper are: atom-ph