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stat.ML2026
Smoothness Adaptivity in Constant-Depth Neural Networks: Optimal Rates via Smooth Activations
Yuhao Liu, Zilin Wang, Lei Wu +1
Smooth activation functions are ubiquitous in modern deep learning, yet their theoretical advantages over non-smooth counterparts remain poorly understood. In this work, we study b…
stat.ML2026
Optimal Learning Rate Schedules under Functional Scaling Laws: Power Decay and Warmup-Stable-Decay
Binghui Li, Zilin Wang, Fengling Chen +3
We study optimal learning rate (LR) schedules under the functional scaling law (FSL) framework (Li et al., 2025), which decomposes training dynamics into signal learning and noise…