SML:Enhance the Network Smoothness with Skip Meta Logit for CTR Prediction. (arXiv:2210.10725v1 [cs.IR])

In light of the smoothness property brought by skip connections in ResNet,
this paper proposed the Skip Logit to introduce the skip connection mechanism
that fits arbitrary DNN dimensions and embraces similar properties to ResNet.
Meta Tanh Normalization (MTN) is designed to learn variance information and
stabilize the training process. With these delicate designs, our Skip Meta
Logit (SML) brought incremental boosts to the performance of extensive SOTA ctr
prediction models on two real-world datasets. In the meantime, we prove …

arxiv meta network prediction sml