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IDSS Special Seminars Jacob Steinhardt

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Provably Secure Machine Learning

Jacob Steinhardt (Stanford)
32-G449 (Kiva/Patel)

Abstract:  The widespread use of machine learning systems creates a new class of computer security vulnerabilities where, rather than attacking the integrity of the software itself, malicious actors exploit the statistical nature of the learning algorithms. For instance, attackers can add fake data (e.g. by creating fake user accounts), or strategically manipulate inputs to the system…

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