1 citations · 1 across the 3 of their papers we have counts for
3 papers
stat.ML2022
On uniform-in-time diffusion approximation for stochastic gradient descent
Lei Li, Yuliang Wang
The diffusion approximation of stochastic gradient descent (SGD) in current literature is only valid on a finite time interval. In this paper, we establish the uniform-in-time diff…
math.PR2022★ 1 cited
A sharp uniform-in-time error estimate for Stochastic Gradient Langevin Dynamics
Lei Li, Yuliang Wang
We establish a sharp uniform-in-time error estimate for the Stochastic Gradient Langevin Dynamics (SGLD), which is a widely-used sampling algorithm. Under mild assumptions, we obta…
math.OC2019
On the convergence of gradient descent for two layer neural networks
Lei Li
It has been shown that gradient descent can yield the zero training loss in the over-parametrized regime (the width of the neural networks is much larger than the number of data po…