[D] Self-supervised learning vs denoising autoencoder
How different is Self-supervised learning to Denoising Autoencoder? Is it like 2019 rebrand?
- Both need cleverly hand-engineered noise as input. This is the meta-label.
- Labels are free, because labels are the original inputs themselves.
- Unsupervised-as-supervised learning
- Remove, change part of inputs (colors, rotation, pixels, words), then predict what is missing, what is original.
- Learnt embeddings become free feature extractor.
How about minimax game to noise and denoise? Can we do something with training frameworks like Actor-Critic, GAN, and PowerPlay ?