1 citations · 1 across the 2 of their papers we have counts for
2 papers
stat.ML2023
Global Optimality of Elman-type RNN in the Mean-Field Regime
Andrea Agazzi, Jianfeng Lu, Sayan Mukherjee
We analyze Elman-type Recurrent Reural Networks (RNNs) and their training in the mean-field regime. Specifically, we show convergence of gradient descent training dynamics of the R…
math.OC2023★ 1 cited
A Policy Gradient Framework for Stochastic Optimal Control Problems with Global Convergence Guarantee
Mo Zhou, Jianfeng Lu
We consider policy gradient methods for stochastic optimal control problem in continuous time. In particular, we analyze the gradient flow for the control, viewed as a continuous t…