most citedLearning to Simulate Daily Activities via Modeling Dynamic Human Needs

29 citations · 39 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2023

Detecting Vulnerable Nodes in Urban Infrastructure Interdependent Network

Jinzhu Mao, Liu Cao, Chen Gao +4

Understanding and characterizing the vulnerability of urban infrastructures, which refers to the engineering facilities essential for the regular running of cities and that exist n…

cs.LG20232 cited

Origin-Destination Network Generation via Gravity-Guided GAN

Can Rong, Huandong Wang, Yong Li

Origin-destination (OD) flow, which contains valuable population mobility information including direction and volume, is critical in many urban applications, such as urban planning…

cs.AI20238 cited

Advancements in Federated Learning: Models, Methods, and Privacy

Huiming Chen, Huandong Wang, Qingyue Long +2

Federated learning (FL) is a promising technique for addressing the rising privacy and security issues. Its main ingredient is to cooperatively learn the model among the distribute…

cs.LG202329 cited

Learning to Simulate Daily Activities via Modeling Dynamic Human Needs

Yuan Yuan, Huandong Wang, Jingtao Ding +2

Daily activity data that records individuals' various types of activities in daily life are widely used in many applications such as activity scheduling, activity recommendation, a…

cs.NI2014

Virtual Machine Migration Planning in Software-Defined Networks

Huandong Wang, Yong Li, Ying Zhang +1

In this paper, we examine the problem of how to schedule the migrations and how to allocate network resources for migration when multiple VMs need to be migrated at the same time.…