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Faculty Candidate
Faculty Candidate Talk: Adaptive Adversarial Learning for a Diverse Visual World
Newell-Simon Hall 3305Areas of Interest: Computer vision and machine learning Abstract Automated visual recognition is in increasingly high demand. However, despite tremendous performance improvement in recent years, state-of-the-art deep visual models learned using large-scale benchmark datasets still fail to generalize to the diverse visual world. In this talk I will discuss a general purpose semi-supervised learning algorithm, [...]