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cs.CV2023★ 11 cited
Learning the Relation between Similarity Loss and Clustering Loss in Self-Supervised Learning
Jidong Ge, Yuxiang Liu, Jie Gui +5
Self-supervised learning enables networks to learn discriminative features from massive data itself. Most state-of-the-art methods maximize the similarity between two augmentations…
cs.CV2021
Delving into Variance Transmission and Normalization: Shift of Average Gradient Makes the Network Collapse
Yuxiang Liu, Jidong Ge, Chuanyi Li +1
Normalization operations are essential for state-of-the-art neural networks and enable us to train a network from scratch with a large learning rate (LR). We attempt to explain the…