6 citations · 29 across the 24 of their papers we have counts for
4 papers · 2 filters
On the Analysis of Model-free Methods for the Linear Quadratic Regulator
Zeyu Jin, Johann Michael Schmitt, Zaiwen Wen
Many reinforcement learning methods achieve great success in practice but lack theoretical foundation. In this paper, we study the convergence analysis on the problem of the Linear…
Enhance Curvature Information by Structured Stochastic Quasi-Newton Methods
Minghan Yang, Dong Xu, Hongyu Chen +2
In this paper, we consider stochastic second-order methods for minimizing a finite summation of nonconvex functions. One important key is to find an ingenious but cheap scheme to i…
Sketchy Empirical Natural Gradient Methods for Deep Learning
Minghan Yang, Dong Xu, Zaiwen Wen +2
In this paper, we develop an efficient sketchy empirical natural gradient method (SENG) for large-scale deep learning problems. The empirical Fisher information matrix is usually l…
A Trust-Region Method For Nonsmooth Nonconvex Optimization
Ziang Chen, Andre Milzarek, Zaiwen Wen
We propose a trust-region type method for a class of nonsmooth nonconvex optimization problems where the objective function is a summation of a (probably nonconvex) smooth function…