1 citations · 1 across the 4 of their papers we have counts for
4 papers
Long-Run Dynamics of AdaGrad-Norm: Trajectory Stability and Asymptotic Stationarity
Ruinan Jin, Xiaoyu Wang
AdaGrad-Norm is widely studied, yet its long-run behavior in smooth nonconvex optimization remains delicate. For the standard current-denominator recursion, the same stochastic gra…
Discontinuous hybrid neural networks for the one-dimensional partial differential equations
Xiaoyu Wang, Long Yuan, Yao Yu
A feedforward neural network, including hidden layers, motivated by nonlinear functions (such as Tanh, ReLU, and Sigmoid functions), exhibits uniform approximation properties in So…
Quantitative Error Bounds for Scaling Limits of Stochastic Iterative Algorithms
Xiaoyu Wang, Mikolaj J. Kasprzak, Jeffrey Negrea +2
Stochastic iterative algorithms, including stochastic gradient descent (SGD) and stochastic gradient Langevin dynamics (SGLD), are widely utilized for optimization and sampling in…
Stability and convergence analysis of AdaGrad for non-convex optimization via novel stopping time-based techniques
Ruinan Jin, Xiaoyu Wang, Baoxiang Wang
Adaptive gradient optimizers (AdaGrad), which dynamically adjust the learning rate based on iterative gradients, have emerged as powerful tools in deep learning. These adaptive met…