6 citations · 6 across the 1 of their papers we have counts for
3 papers
cs.LG2020★ 6 cited
Learning Over-Parametrized Two-Layer ReLU Neural Networks beyond NTK
Yuanzhi Li, Tengyu Ma, Hongyang R. Zhang
We consider the dynamic of gradient descent for learning a two-layer neural network. We assume the input is drawn from a Gaussian distribution and the label of $…
cs.LG2019
Towards Explaining the Regularization Effect of Initial Large Learning Rate in Training Neural Networks
Yuanzhi Li, Colin Wei, Tengyu Ma
Stochastic gradient descent with a large initial learning rate is widely used for training modern neural net architectures. Although a small initial learning rate allows for faster…
cs.LG2018
Algorithmic Framework for Model-based Deep Reinforcement Learning with Theoretical Guarantees
Yuping Luo, Huazhe Xu, Yuanzhi Li +3
Model-based reinforcement learning (RL) is considered to be a promising approach to reduce the sample complexity that hinders model-free RL. However, the theoretical understanding…