most citedObstacle Avoidance and Navigation Utilizing Reinforcement Learning with Reward Shaping

4 citations · 4 across the 3 of their papers we have counts for

collaborators

5 papers

math.OC2021

Accelerated Zeroth-order Algorithm for Stochastic Distributed Nonconvex Optimization

Shengjun Zhang, Colleen P. Bailey

This paper investigates how to accelerate the convergence of distributed optimization algorithms on nonconvex problems with zeroth-order information available only. We propose a ze…

math.OC2021

Accelerated Primal-Dual Algorithm for Distributed Non-convex Optimization

Shengjun Zhang, Colleen P. Bailey

This paper investigates accelerating the convergence of distributed optimization algorithms on non-convex problems. We propose a distributed primal-dual stochastic gradient descent…

math.OC2021

Convergence Analysis of Nonconvex Distributed Stochastic Zeroth-order Coordinate Method

Shengjun Zhang, Yunlong Dong, Dong Xie +3

This paper investigates the stochastic distributed nonconvex optimization problem of minimizing a global cost function formed by the summation of local cost functions. We solve…

cs.RO20204 cited

Obstacle Avoidance and Navigation Utilizing Reinforcement Learning with Reward Shaping

Daniel Zhang, Colleen P. Bailey

In this paper, we investigate the obstacle avoidance and navigation problem in the robotic control area. For solving such a problem, we propose revised Deep Deterministic Policy Gr…

eess.SP2020

Extremal Region Analysis based Deep Learning Framework for Detecting Defects

Zelin Deng, Xiaolong Yan, Shengjun Zhang +1

A maximally stable extreme region (MSER) analysis based convolutional neural network (CNN) for unified defect detection framework is proposed in this paper. Our proposed framework…