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ORCID19th CollaborateCom 2023: Corfu Island, Greece - Part III
- Honghao Gao, Xinheng Wang, Nikolaos S. Voros:
Collaborative Computing: Networking, Applications and Worksharing - 19th EAI International Conference, CollaborateCom 2023, Corfu Island, Greece, October 4-6, 2023, Proceedings, Part III. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 563, Springer 2024, ISBN 978-3-031-54530-6
Onsite Session Day 2
- Peisong Li
, Ziren Xiao, Xinheng Wang, Kaizhu Huang, Yi Huang, Andrei Tchernykh:
Multi-agent Reinforcement Learning Based Collaborative Multi-task Scheduling for Vehicular Edge Computing. 3-22 - Zhenchao Ouyang, Jiahe Cui, Yunxiang He, Dongyu Li, Qinglei Hu, Changjie Zhang:
A Novel Topology Metric for Indoor Point Cloud SLAM Based on Plane Detection Optimization. 23-40 - Godwin Idoje, Tasos Dagiuklas, Muddesar Iqbal:
On the Performance of Federated Learning Network. 41-56
Federated Learning and Application
- Yan Zeng, Hui Zheng, Xin Wang, Beibei Zhang, Mingyao Zhou, Jilin Zhang, Yongjian Ren:
FedECCR: Federated Learning Method with Encoding Comparison and Classification Rectification. 59-78 - Dun Cao, Jiasi Xiong, Nanfang Lei, Robert Simon Sherratt, Jin Wang:
CSA_FedVeh: Cluster-Based Semi-asynchronous Federated Learning Framework for Internet of Vehicles. 79-99 - Junfeng Hao, Juan Chen, Peng Chen, Yang Wang, Xianhua Niu, Lei Xu, Yunni Xia:
Efficiently Detecting Anomalies in IoT: A Novel Multi-Task Federated Learning Method. 100-117 - Zhaobin Ouyang, Yunni Xia, Qinglan Peng, Yin Li, Peng Chen, Xu Wang:
A Novel Deep Federated Learning-Based and Profit-Driven Service Caching Method. 118-133 - Zhongqin Bi, Yutang Duan, Weina Zhang, Meijing Shan:
A Multi-behavior Recommendation Algorithm Based on Personalized Federated Learning. 134-153 - Lamir Shkurti, Mennan Selimi, Adrian Besimi:
FederatedMesh: Collaborative Federated Learning for Medical Data Sharing in Mesh Networks. 154-169
Collaborative Working
- Chaonong Xu, Yujie Jiang:
Enhance Broadcasting Throughput by Associating Network Coding with UAVs Relays Deployment in Emergency Communications. 173-190 - Linxin Guo, Shiqi Wang, Min Gao, Chongming Gao:
Dynamic Target User Selection Model for Market Promotion with Multiple Stakeholders. 191-207 - Xiangpei Yan, Xiao Xue, Chao Peng, Donghua Liu, Zhiyong Feng, Xiao Wang:
Collaborative Decision-Making Processes Analysis of Service Ecosystem: A Case Study of Academic Ecosystem Involution. 208-228 - Robin Kraft, Maximilian Blasi, Marc Schickler, Manfred Reichert, Rüdiger Pryss:
Operationalizing the Use of Sensor Data in Mobile Crowdsensing: A Systematic Review and Practical Guidelines. 229-248 - Myriel Fichtner, Sascha Sucker, Dominik Riedelbauch, Stefan Jablonski, Dominik Henrich:
Enriching Process Models with Relevant Process Details for Flexible Human-Robot Teaming. 249-269
Edge Computing
- Lei Shi, Rui Ji, Zhen Wei, Shilong Feng, Zhehao Li:
Joint Optimization of PAoI and Queue Backlog with Energy Constraints in LoRa Gateway Systems. 273-290 - Cairong Yan, Yiwei Zhang, Xiangyang Feng, Yanglan Gan:
Enhancing Session-Based Recommendation with Multi-granularity User Interest-Aware Graph Neural Networks. 291-307 - Junyi Xu, Zhenchun Wei, Xiaohui Yuan, Zengwei Lyu, Lin Feng, Jianghong Han:
Delay-Constrained Multicast Throughput Maximization in MEC Networks for High-Speed Railways. 308-328 - Qi Yu, Weilong Ding, Maoxiang Sun, Jihai Huang:
An Evolving Transformer Network Based on Hybrid Dilated Convolution for Traffic Flow Prediction. 329-343
Prediction, Optimization and Applications
- Dingkang Han, Yujia Zhu, Liang Jiao, Dikai Mo, Yong Sun, Yuedong Zhang, Qingyun Liu:
DualDNSMiner: A Dual-Stack Resolver Discovery Method Based on Alias Resolution. 347-364 - Ruiqi Liu, Min Gao, Yujiang Wu, Jie Zeng, Jia Zhang, Jinyong Gao:
DT-MUSA: Dual Transfer Driven Multi-source Domain Adaptation for WEEE Reverse Logistics Return Prediction. 365-384 - Yanguo Zeng, Meiting Xue, Peiran Xu, Yukun Shi, Kaisheng Zeng, Jilin Zhang, Lupeng Yue:
A Synchronous Parallel Method with Parameters Communication Prediction for Distributed Machine Learning. 385-403
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