Abstract
The chapter describes the structure and outcomes of the NIPS 2017 competition focused on generating and defending against adversarial examples in machine learning classifiers.
AI-generated summary
To accelerate research on adversarial examples and robustness of machine learning classifiers, Google Brain organized a NIPS 2017 competition that encouraged researchers to develop new methods to generate adversarial examples as well as to develop new ways to defend against them. In this chapter, we describe the structure and organization of the competition and the solutions developed by several of the top-placing teams.
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