13 citations · 24 across the 8 of their papers we have counts for
8 papers
Globally Convergent Policy Gradient Methods for Linear Quadratic Control of Partially Observed Systems
Feiran Zhao, Xingyun Fu, Keyou You
While the optimization landscape of policy gradient methods has been recently investigated for partially observed linear systems in terms of both static output feedback and dynamic…
Convergence and Sample Complexity of Policy Gradient Methods for Stabilizing Linear Systems
Feiran Zhao, Xingyun Fu, Keyou You
System stabilization via policy gradient (PG) methods has drawn increasing attention in both control and machine learning communities. In this paper, we study their convergence and…
Learning Stabilizing Controllers of Linear Systems via Discount Policy Gradient
Feiran Zhao, Xingyun Fu, Keyou You
Stability is one of the most fundamental requirements for systems synthesis. In this paper, we address the stabilization problem for unknown linear systems via policy gradient (PG)…
An FEA surrogate model with Boundary Oriented Graph Embedding approach
Xingyu Fu, Fengfeng Zhou, Dheeraj Peddireddy +3
In this work, we present a Boundary Oriented Graph Embedding (BOGE) approach for the Graph Neural Network (GNN) to serve as a general surrogate model for regressing physical fields…
AlphaGomoku: An AlphaGo-based Gomoku Artificial Intelligence using Curriculum Learning
Zheng Xie, XingYu Fu, JinYuan Yu
In this project, we combine AlphaGo algorithm with Curriculum Learning to crack the game of Gomoku. Modifications like Double Networks Mechanism and Winning Value Decay are impleme…
A Machine Learning Framework for Stock Selection
XingYu Fu, JinHong Du, YiFeng Guo +3
This paper demonstrates how to apply machine learning algorithms to distinguish good stocks from the bad stocks. To this end, we construct 244 technical and fundamental features to…