Live Machine Learning Research - Plain Self-Ensembles - Part 1

Embark on a live machine learning research journey exploring the concept of Plain Self-Ensembles in this engaging video. Follow along as the implementation of a research idea unfolds, focusing on building an ensemble model using students of label-free self-distillation without additional data or augmentation. Discover the surprising effectiveness of this approach and the intriguing correlation between the number of students and improved accuracy. Delve into the hypothesis that challenges the traditional understanding of ensemble effects in relation to label information extraction. The video covers the entire process, from introducing the research idea and adjusting the codebase to creating teacher and student models, deploying to a server, analyzing results, and drawing conclusions. Gain insights into cutting-edge machine learning techniques and witness the excitement of real-time discovery in this comprehensive exploration of Plain Self-Ensembles.