Journal/Magazine Papers

  1. W. Gong, L. Cao, Y. Zhu, F. Zuo, X. He, H. Zhou, “Federated Inverse Reinforcement Learning for Smart ICUs with Differential Privacy“, in IEEE Internet of Things Journal, 2023
  2. C. Wu, Y. Zhu, R. Zhang, Y. Chen, F. Wang, S. Cui, “FedAB: Truthful Federated Learning with Auction-based Combinatorial Multi-Armed Bandit“, in IEEE Internet of Things Journal, 2023
  3. B. Zhu, S. Lin, Y. Zhu, X. Wang, “Collaborative Hyperspectral Image Processing using Satellite Edge Computing“, in IEEE Transactions on Mobile Computing, 2023. (CCF-A)
  4. S. Shi, C. Hu, D. Wang, Y. Zhu, Z. Han, “Federated HD Map Updating through Overlapping Coalition Formation Game“, in IEEE Transactions on Mobile Computing, 2023. (CCF-A)
  5. D. Chen, Y. Zhu, D. Wang, H. Wang, J. Xie, X. Zhang, Z. Han, “Love of Variety based Latency Analysis for High Definition Map Updating: Age of Information and Distributional Robust Perspectives“, in IEEE Transactions on Intelligent Vehicles, 2022
  6. Z. Wang, Y. Zhu, D. Wang, Z. Han, “Secure Trajectory Publication in Untrusted Environments: A Federated Analytics Approach“, in IEEE Transactions on Mobile Computing, 2022. (CCF-A)
  7. Z. Wang, Y. Zhu, D. Wang, Z. Han, “Federated Analytics Informed Distributed Industrial IoT Learning with Non-IID Data“, in IEEE Transactions on Network Science and Engineering, 2022.
  8. T. Wang, S. Chen, Y. Zhu, A. Tang, and X. Wang, “LinkSlice: Fine-grained Network Slice Enforcement Based on Deep Reinforcement Learning“, in IEEE Journal on Selected Areas in Communications, 2022. (CCF-A)
  9. M. Zhang, Y. Zhu, J. Liu, F. Wang, F. Wang, “CharmSeeker: Automated Pipeline Configuration for Serverless Video Processing“, in IEEE/ACM Transaction on Networking, 2022. (CCF-A)
  10. J. Zhang, S. Chen, X. Wang, Y. Zhu, “Dynamic Reservation of Edge Servers via Deep Reinforcement Learning for Connected Vehicles“, in IEEE Transactions on Mobile Computing, 2021. (CCF-A)
  11. D. Wang, S. Shi, Y. Zhu, Z. Han. “Federated Analytics: Opportunities and Challenges“,  in IEEE Network, 2021.
  12. M. Zhang, F. Wang, Y. Zhu, J. Liu, B. Li. “Serverless Empowered Video Analytics for Ubiquitous Networked Cameras“,  in IEEE Network, 2021.
  13. S. Shi, C. Hu, D. Wang, Y. Zhu, Z. Han, “Federated Anomaly Analytics for Local Model Poisoning Attack“, in IEEE Journal on Selected Areas in Communications, 2021. (CCF-A)
  14. D. Chen, D. Wang, Z. Han, Y. Zhu, “Digital Twin for Federated Analytics Using A Bayesian Approach“, in IEEE Internet of Things Journal, 2021
  15. F. Wang, C. Zhang, F. Wang, J. Liu, Y. Zhu, H. Pang, L. Sun, “DeepCast: Towards Personalized QoE for Edge-Assisted Crowdcast With Deep Reinforcement Learning“, in IEEE/ACM Transaction on Networking, 2020 (CCF-A)
  16. F. Wang, Y. Zhu, F. Wang, J. Liu, X. Ma, X. Fan.  “Car4Pac: Last Mile Parcel Delivery through Intelligent Car Trip Sharing“, in IEEE Transactions on Intelligent Transportation Systems, 2019.
  17. Y. Zhu, Q. He, J. Liu, B. Li, Y. Hu. “When Crowd Meets Big Video Data: Cloud-Edge Collaborative Transcoding for Personal Livecast“, in IEEE Transactions on Network Science and Engineering, 2018.
  18. Y. Zhu, S. Fu, J. Liu, Y. Cui. “Truthful Online Auction Towards Maximized Instance Utilization in the Cloud“, in IEEE/ACM Transaction on Networking, 2018. (CCF-A)

Conference Papers

  1. D. Song, C. Zhang, Y. Zhu, J. Liu, “LiGo: A Low Cost Cross-Platform Deployment Framework Empowers Video Processing Application“, to appear in ACM NOSSDAV 2023
  2. Q. Pan, Y. Zhu, L. Chu, “Lumos: Heterogeneity-aware Federated Graph Learning over Decentralized Devices“, to appear in IEEE ICDE 2023 (CCF-A)
  3. M. Zhang, Y. Zhu, L. Shen, F. Wang, J. Liu, “OmniSense: Towards Edge-Assisted Online Analytics for 360-Degree Videos“, to appear in IEEE INFOCOM 2023 (CCF-A)
  4. C. Wu, Y. Zhu, F. Wang, “DSFL: Decentralized Satellite Federated Learning for Energy-Aware LEO Constellation Computing“, in IEEE Satellite 2022  (Best Student Paper Award)
  5. Y. Zhu, W. Bao, D. Wang, J. Liu. “A Stackelberg Queuing Model and Analysis for the Emerging Connection-based Pricing in IoT Markets“,  in IEEE MASS, 2022
  6. K. Chen, Y. Zhu, Z. Han, X. Wang. “Adaptive Cross-Camera Video Analytics at the Edge“, in IEEE MASS, 2022
  7. K. Chen, Y. Zhu, Y. Kang, Z. Han. “Few-Shot Correlation Estimation for Cross-Camera Video Analytics: A Mean-Field Game Approach“, in IEEE PIMRC, Native-AI in wireless networks workshop, 2022
  8. C. Tang, K. Ouyang, Z. Wang, Y. Zhu, W. Ji, Y. Wang, W. Zhu. “Mixed-Precision Neural Network Quantization via Learned Layer-wise Importance“, in ECCV 2022
  9. Y. Lu, Y. Zhu, Z. Wang. “Personalized 360-Degree Video Streaming: A Meta-Learning Approach“, in ACM Multimedia, 2022 (CCF-A)
  10. C. Tang, H. Zhai, K. Ouyang, Z. Wang, Y. Zhu, W. Zhu. “Arbitrary Bit-width Network: A Joint Layer-Wise Quantization and Adaptive Inference Approach“,  in ACM Multimedia, 2022 (CCF-A)
  11. Q. Pan, Y. Zhu. “FedWalk: Communication Efficient Federated Unsupervised Node Embedding with Differential Privacy“, in ACM SIGKDD, 2022 (CCF-A)
  12. X. Yuan, M. Wu, Z. Wang, Y. Zhu, M. Ma, J. Guo, Z. Zhang, W. Zhu. “Understanding 5G Performance for Real-world Services: a Content Provider’s Perspective“,  in ACM SIGCOMM, 2022 (CCF-A)
  13. S. Shi, C. Hu, D. Wang, Y. Zhu, Z Han. “Distributionally Robust Federated Learning for Differentially Private Data“, in IEEE ICDCS, 2022
  14. H. Cao, Q. Pan, Y. Zhu, J. Liu.”Birds of a Feather Help: Context-aware Client Selection for Federated Learning“,  in International Workshop on Trustable, Verifiable and Auditable Federated Learning in Conjunction with AAAI 2022
  15. Z. Wang, Y. Zhu, D. Wang, Z. Han. “FedFPM: A Unified Federated Analytics Framework for Collaborative Frequent Pattern Mining“, in IEEE INFOCOM, 2022 (CCF-A)
  16. S. Xie, Y. Xue, Y. Zhu, Z. Wang. “Cost Effective MLaaS Federation: A Combinatorial Reinforcement Learning Approach“,  in IEEE INFOCOM, 2022 (CCF-A)
  17. M. Zhang, F. Wang, Y. Zhu, J. Liu, Z. Wang. “Towards Cloud-Edge Collaborative Online Video Analytics with Fine-Grained Serverless Pipelines“, in ACM MMSys, 2021.
  18. Z. Wang, Y. Zhu, D. Wang, Z. Han. “FedACS: Federated Skewness Analytics in Heterogeneous Decentralized Data Environments“, in IEEE/ACM IWQoS, 2021
  19. J. Zhang, S. Chen, X. Wang, Y. Zhu. “DeepReserve: Dynamic Edge Server Reservation for Connected Vehicles with Deep Reinforcement Learning“, in IEEE INFOCOM, 2021 (CCF-A)
  20. M. Zhang, Y. Zhu, C. Zhang, J. Liu. “Video processing with serverless computing: a measurement study“, in ACM NOSSDAV, 2019
  21. F. Wang, C. Zhang, J. Liu, Y. Zhu, H. Pang, L. Sun. “Intelligent Edge-Assisted Crowdcast with Deep Reinforcement Learning for Personalized QoE“, in IEEE INFOCOM, 2019 (CCF-A)
  22. Y. Huang, Y. Zhu, X. Fan, X. Ma, F. Wang, J. Liu, Z. Wang, Y. Cui. “Task Scheduling with Optimized Transmission Time in Collaborative Cloud-Edge Learning“, in IEEE ICCCN, 2018
  23. F. Wang, Y. Zhu, F. Wang, J. Liu. “Ridesharing as a Service: Exploring Crowdsourced Connected Vehicle Information for Intelligent Package Delivery“, in IEEE/ACM IWQoS, 2018
  24. Y. Zhu, J. Liu, Z. Wang, C. Zhang. “When Cloud Meets Uncertain Crowd: An Auction Approach for Crowdsourced Livecast Transcoding“, in ACM Multimedia, 2017 (CCF-A)
  25. S. Fu, Y. Zhu, J. Liu. “HARV: Harnessing hybrid virtualization to improve instance (re) usage in public cloud“, in IEEE/ACM IWQoS, 2017
  26. Y. Zhu, S. Fu, J. Liu, Y. Cui. “Truthful Online Auction for Cloud Instance Subletting“, in IEEE ICDCS, 2017
  27. Y. Zhu, J. Jiang, B. Li, B. Li. “Rado: A Randomized Auction Approach for Data Offloading via D2D Communication“, in IEEE MASS, 2015
  28. J. Jiang, Y. Zhu, B. Li, B. Li. “Rally: Device-to-device content sharing in LTE networks as a game“, IEEE MASS, 2015

Demos and Posters

  1. D. Song, Y. Zhu, C. Zhang, J. Liu. “Trueno: A Cross-Platform Machine Learning Model Serving Framework in Heterogeneous Edge Systems“, in IEEE INFOCOM 2022
  2. Y. Zhu, J. Liu. “C2: Procuring uncertain freelancers for interactive live video transcoding“, in IEEE/ACM IWQoS 2017