3 papers
cs.LG2025
Theoretical Analysis on how Learning Rate Warmup Accelerates Convergence
Yuxing Liu, Yuze Ge, Rui Pan +2
Learning rate warmup is a popular and practical technique in training large-scale deep neural networks. Despite the huge success in practice, the theoretical advantages of this str…
math.OC2024
SOREL: A Stochastic Algorithm for Spectral Risks Minimization
Yuze Ge, Rujun Jiang
The spectral risk has wide applications in machine learning, especially in real-world decision-making, where people are not only concerned with models' average performance. By assi…
math.OC2023
A Unified Framework for Rank-based Loss Minimization
Rufeng Xiao, Yuze Ge, Rujun Jiang +1
The empirical loss, commonly referred to as the average loss, is extensively utilized for training machine learning models. However, in order to address the diverse performance req…