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URL:/computer-science/events/seminar-machine-learning-n
 ew-advances-in-adversarially-robust-and-secure-machine-learning
SUMMARY:Seminar • Machine Learning — New Advances in (Adversarially)\nR
 obust and Secure Machine Learning
CLASS:PUBLIC
DESCRIPTION:Summary \n\nPLEASE NOTE: THIS SEMINAR WILL BE GIVEN ONLINE.\n\n
 HONGYANG ZHANG\, POSTDOCTORAL FELLOW\n_Toyota Technological Institute at 
 Chicago_\n\nDeep learning models are often vulnerable to adversarial examp
 les. In\nthis talk\, we will focus on robustness and security of machine\n
 learning against adversarial examples. There are two types of defenses\nag
 ainst such attacks: 1) empirical and 2) certified adversarial\nrobustness.
 \n 
DTSTAMP:20250528T173047Z
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