this post was submitted on 12 Jun 2023
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Machine Learning
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I had the pleasure of conducting research into self-supervised learning (SSL) for computer vision.
What stood out to me was the simplicity of the SSL algorithms combined with the astonishing performance of the self-supervisedly trained models after supervised fine-tuning.
Also the fact that SSL works across tasks and domains, e.g., text generation, image generation, semantic segmentation...
I too believe that SSL (and to some extent Unsupervised Learning) is by far the best way to frame learning problems in DL, it has shown to avoid the pesky mode collapse and improves out of distribution inference performance.