Overview
Explore adversarial self-supervised contrastive learning in this 43-minute lecture from the University of Central Florida. Delve into the background of self-supervised learning, examine contrastive learning transformers and frameworks, and understand the contrastive learning algorithm. Learn about linear evaluation techniques, including robust linear evaluation, and analyze experiments, ablation studies, and robustness studies. Gain valuable insights into this cutting-edge machine learning approach and its applications in the field of artificial intelligence.
Syllabus
Presentation
Background
Selfsupervised learning
Contrastive learning transformers
Contrastive learning framework
Contrastive learning algorithm
Linear evaluation
Robust linear evaluation
Experiments
Ablation Studies
Robustness Studies
Conclusion
Taught by
UCF CRCV