Explore the concept of contrastive learning with adversarial examples in this 31-minute lecture from the University of Central Florida. Delve into paper details, unsupervised embedding techniques, and self-supervised learning approaches. Examine experiments, baseline comparisons, and ablation studies to understand the effectiveness of the proposed methods. Analyze the architecture study and conclude with a discussion on the strengths of this approach in machine learning and computer vision.
Contrastive Learning with Adversarial Examples - Spring 2021
University of Central Florida via YouTube
Overview
Syllabus
Introduction
Paper Details
Overview
Unsupervised Embedding
Selfsupervised Learning
Experiments
Baseline Comparison
Ablation Study
Architecture Study
Conclusion
Strengths
Taught by
UCF CRCV
Tags
Related Courses
-
Adversarial Self-Supervised Contrastive Learning
-
Introduction to Machine Learning with Python
-
Robust Pre-Training by Adversarial Contrastive Learning - CAP6412 Spring 2021
-
AI and Machine Learning Algorithms and Techniques
-
Machine Learning for Semiconductor Quantum Devices
-
Big Self-Supervised Models Are Strong Semi-Supervised Learners
