3 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.LG2025
SoftSignSGD(S3): An Enhanced Optimizer for Practical DNN Training and Loss Spikes Minimization Beyond Adam
Hanyang Peng, Shuang Qin, Yue Yu +3
Adam has proven remarkable successful in training deep neural networks, but the mechanisms underlying its empirical successes and limitations remain underexplored. In this study, w…
cs.LG2025
Simple Convergence Proof of Adam From a Sign-like Descent Perspective
Hanyang Peng, Shuang Qin, Yue Yu +3
Adam is widely recognized as one of the most effective optimizers for training deep neural networks (DNNs). Despite its remarkable empirical success, its theoretical convergence an…
cs.CR2023★ 3 cited
Practical Privacy-Preserving Gaussian Process Regression via Secret Sharing
Jinglong Luo, Yehong Zhang, Jiaqi Zhang +4
Gaussian process regression (GPR) is a non-parametric model that has been used in many real-world applications that involve sensitive personal data (e.g., healthcare, finance, etc.…