6 citations · 22 across the 15 of their papers we have counts for
22 papers · 1 filter
A counterexample to global convergence of classical DFP under the standard strong Wolfe conditions
Benqi Liu, Zichen Wang, Zaiwen Wen +2
A long-standing open question in quasi-Newton optimization asks whether the classical Davidon--Fletcher--Powell (DFP) method converges globally on uniformly convex objectives when…
On the Optimal Lower and Upper Complexity Bounds for a Class of Composite Optimization Problems
Zhenyuan Zhu, Fan Chen, Junyu Zhang +1
We study the optimal lower and upper complexity bounds for finding approximate solutions to the composite problem , where is smooth and is convex. Giv…
Monte Carlo Policy Gradient Method for Binary Optimization
Cheng Chen, Ruitao Chen, Tianyou Li +2
Binary optimization has a wide range of applications in combinatorial optimization problems such as MaxCut, MIMO detection, and MaxSAT. However, these problems are typically NP-har…
The Error in Multivariate Linear Extrapolation with Applications to Derivative-Free Optimization
Liyuan Cao, Zaiwen Wen, Ya-xiang Yuan
We study in this paper the function approximation error of multivariate linear extrapolation. The sharp error bound of linear interpolation already exists in the literature. Howeve…
NG+ : A Multi-Step Matrix-Product Natural Gradient Method for Deep Learning
Minghan Yang, Dong Xu, Qiwen Cui +2
In this paper, a novel second-order method called NG+ is proposed. By following the rule ``the shape of the gradient equals the shape of the parameter", we define a generalized fis…
A Stochastic Composite Augmented Lagrangian Method For Reinforcement Learning
Yongfeng Li, Mingming Zhao, Weijie Chen +1
In this paper, we consider the linear programming (LP) formulation for deep reinforcement learning. The number of the constraints depends on the size of state and action spaces, wh…