activity
20192022
most citedFinite-sample Analysis of Greedy-GQ with Linear Function Approximation under Markovian Noise

8 citations · 26 across the 5 of their papers we have counts for

collaborators

7 papers

eess.SP20227 cited

Distributed Swarm Learning for Internet of Things at the Edge: Where Artificial Intelligence Meets Biological Intelligence

Yue Wang, Zhi Tian, Xin Fan +3

With the proliferation of versatile Internet of Things (IoT) services, smart IoT devices are increasingly deployed at the edge of wireless networks to perform collaborative machine…

cs.LG20222 cited

Robust Distributed Learning Against Both Distributional Shifts and Byzantine Attacks

Guanqiang Zhou, Ping Xu, Yue Wang +1

In distributed learning systems, robustness issues may arise from two sources. On one hand, due to distributional shifts between training data and test data, the trained model coul…

cs.LG20216 cited

Online Robust Reinforcement Learning with Model Uncertainty

Yue Wang, Shaofeng Zou

Robust reinforcement learning (RL) is to find a policy that optimizes the worst-case performance over an uncertainty set of MDPs. In this paper, we focus on model-free robust RL, w…

cs.LG2021

Non-Asymptotic Analysis for Two Time-scale TDC with General Smooth Function Approximation

Yue Wang, Shaofeng Zou, Yi Zhou

Temporal-difference learning with gradient correction (TDC) is a two time-scale algorithm for policy evaluation in reinforcement learning. This algorithm was initially proposed wit…

cs.LG20213 cited

1-Bit Compressive Sensing for Efficient Federated Learning Over the Air

Xin Fan, Yue Wang, Yan Huo +1

For distributed learning among collaborative users, this paper develops and analyzes a communication-efficient scheme for federated learning (FL) over the air, which incorporates 1…

cs.LG20208 cited

Finite-sample Analysis of Greedy-GQ with Linear Function Approximation under Markovian Noise

Yue Wang, Shaofeng Zou

Greedy-GQ is an off-policy two timescale algorithm for optimal control in reinforcement learning. This paper develops the first finite-sample analysis for the Greedy-GQ algorithm w…