https://cis.temple.edu/~jiewu/research/publications/Publication_files/Paper%206750%20Camera%20Ready%20Version.pdf
These methods assign models based on device capabilities and use a semi-asynchronous ap-proach where the server aggregates the earliest received up-dates, bypassing the wait for all clients. This strategy better accommodates various devices and improves FL efficiency.
https://cis.temple.edu/~wu/research/publications/Publication_files/Social-Aware%20DT-Assisted%20Service%20Provisioning%20in%20Serverless%20Edge%20Computing.pdf
Social-Aware DT-Assisted Service Provisioning in Serverless Edge Computing Jing Li†, Jianping Wang†, Weifa Liang†, Jie Wu¶, Quan Chen§, and Zichuan Xu$ † Department of Computer Science, City University of Hong Kong, Hong Kong, P. R. China ¶ Department of Computer and Information Sciences, Temple University, Philadelphia, USA
https://cis.temple.edu/~latecki/Courses/CIS2033-Spring12/ElementaryProbabilityforApplications/ch2.pdf
To work up to the solution we begin with something that is obvious but is a key step in some of the reasoning to follow.
https://sites.temple.edu/pdames/files/2016/07/DamesTokekarKumarISRR2015.pdf
Abstract Target tracking is a fundamental problem in robotics research and has been the subject of detailed studies over the years. In this paper, we introduce a new formulation, based on the mathematical concept of random finite sets, that allows for tracking an unknown and dynamic number of mobile targets with a team of robots. We show how to employ the Probability Hypothesis Density filter ...
https://cis.temple.edu/~latecki/Courses/CIS750-03/Papers/KalmanFilterSIGGRAPH2001.pdf
An Introduction to the Kalman Filter Greg Welch Gary Bishop
https://cis.temple.edu/~yu/research/FitLoc-infocom16.pdf
We present the first fine-grained and low-cost DfL ap-proach for multiple targets over various areas, named FitLoc, paving the practical application road of DfL in the outdoor environment.
https://cis.temple.edu/~jiewu/research/publications/Publication_files/m37113-chen%20final.pdf
Abstract—Recent years have witnessed the unprecedented performance of convolutional networks in image super-resolution (SR). SR involves upscaling a single low-resolution image to meet application-specific image quality demands, making it vital for mobile devices. However, the excessive computational and memory requirements of SR tasks pose a challenge in mapping SR networks on a single ...
https://cis.temple.edu/~jiewu/research/publications/Publication_files/jiang_www_2020.pdf
The others try to recommend serendipitous items with novel ap-proaches, such as a method with transfer learning [32], a curiosity-theory-based method [26], and an elasticity-driven approach [24].
https://cis.temple.edu/~wu/research/publications/Publication_files/Topology-Aware_Scheduling_Framework_for_Microservice_Applications_in_Cloud.pdf
Abstract—Loosely coupled and highly cohesived microservices running in containers are becoming the new paradigm for application development. Compared with monolithic applications, applications built on microservices architecture can be deployed and scaled independently, which promises to simplify software development and operation. However, the dramatic increase in the scale of microservices ...