activity
20192022
most citedA Cooperative Multi-Agent Reinforcement Learning Framework for Resource Balancing in Complex Logistics Network

41 citations · 43 across the 4 of their papers we have counts for

collaborators

6 papers

cs.LG20221 cited

Dynamic Relation Discovery and Utilization in Multi-Entity Time Series Forecasting

Lin Huang, Lijun Wu, Jia Zhang +2

Time series forecasting plays a key role in a variety of domains. In a lot of real-world scenarios, there exist multiple forecasting entities (e.g. power station in the solar syste…

cs.CV20221 cited

AF: Adaptive Focus Framework for Aerial Imagery Segmentation

Lin Huang, Qiyuan Dong, Lijun Wu +3

As a specific semantic segmentation task, aerial imagery segmentation has been widely employed in high spatial resolution (HSR) remote sensing images understanding. Besides common…

cs.LG2020

Cooperative Policy Learning with Pre-trained Heterogeneous Observation Representations

Wenlei Shi, Xinran Wei, Jia Zhang +4

Multi-agent reinforcement learning (MARL) has been increasingly explored to learn the cooperative policy towards maximizing a certain global reward. Many existing studies take adva…

cs.SE2020

COSEA: Convolutional Code Search with Layer-wise Attention

Hao Wang, Jia Zhang, Yingce Xia +3

Semantic code search, which aims to retrieve code snippets relevant to a given natural language query, has attracted many research efforts with the purpose of accelerating software…

cs.LG2019

Light Multi-segment Activation for Model Compression

Zhenhui Xu, Guolin Ke, Jia Zhang +2

Model compression has become necessary when applying neural networks (NN) into many real application tasks that can accept slightly-reduced model accuracy with strict tolerance to…

cs.MA201941 cited

A Cooperative Multi-Agent Reinforcement Learning Framework for Resource Balancing in Complex Logistics Network

Xihan Li, Jia Zhang, Jiang Bian +2

Resource balancing within complex transportation networks is one of the most important problems in real logistics domain. Traditional solutions on these problems leverage combinato…