1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.LG2024
Parametric -Norm Scaling Calibration
Siyuan Zhang, Linbo Xie
Output uncertainty indicates whether the probabilistic properties reflect objective characteristics of the model output. Unlike most loss functions and metrics in machine learning,…
cs.LG2023
FRGNN: Mitigating the Impact of Distribution Shift on Graph Neural Networks via Test-Time Feature Reconstruction
Rui Ding, Jielong Yang, Feng Ji +2
Due to inappropriate sample selection and limited training data, a distribution shift often exists between the training and test sets. This shift can adversely affect the test perf…
stat.ML2022★ 1 cited
Probability-Dependent Gradient Decay in Large Margin Softmax
Siyuan Zhang, Linbo Xie, Ying Chen
In the past few years, Softmax has become a common component in neural network frameworks. In this paper, a gradient decay hyperparameter is introduced in Softmax to control the pr…