Pythonによる機械学習入門 ～SVMからDeep Learningまで～

Several recent papers have explored self-supervised learning methods for vision transformers (ViT). Key approaches include: 1. Masked prediction tasks that predict masked patches of the input image. 2. Contrastive learning using techniques like MoCo to learn representations by contrasting augmented views of the same image. 3. Self-distillation methods like DINO that distill a teacher ViT into a st

[soratokimitonoaidani]

MNISTって単純な線形SVMでも90%くらいの正解率行くんだ!?　数百次元あるから学習できないかと思ってたわ

[MasaoBlue]

凄い