Task-orient Compression and Communication

Journal Papers:
  • Y. Wang, Y. Wu, S. Ma, and Y. Angela Zhang, Task-Oriented Lossy Compression With Data, Perception, and Classification Constraints, IEEE J. Sel. Areas Commun., accepted, 2025.
  • Z. Mao, L. Sun and Y. Wu, Robust multi-view subspace clustering with missing data by aligning nonlinear manifolds, Pattern Recognition, Vol. 161, 2025.
  • S. M, Z. Sun, B. Shen, Y. Wu, H. Li, and G. Shi Semantic Feature Division Multiple Access for Digital Semantic Broadcast Channels, IEEE Internet of Things Journal, Early Access, 2025.
  • Y. Wu, Y. Shi, S. Ma, C. Jiang, W. Zhang, and K. B. Letaief, Towards Effective and Interpretable Semantic Communications, IEEE Network Magazine, vol. 38, no. 6, pp. 55-62, Nov. 2024.
  • Y. Zhou, Y. Zou, Y. Wu, Y. Shi and Jun Zhang, Machine Learning for Low-Latency Communications, ELSEVIER, eBook ISBN: 9780443220746, Oct. 2024
  • S. Xia, Y. Shi, Y. Zhou, Y. Wu, L. Yang, and K. Letaief, Federated Learning with Massive Random Access, IEEE Trans. Wireless Commun., to vol. 23, no. 10, pp. 13856-13871, Oct. 2024.
  • Y. Yang, Y. Wu, Y. Jiang, and Y. Shi, One-Bit Byzantine-Tolerant Distributed Learning via Over-the-Air Computation, IEEE Trans. Wireless Commun., vol. 23, no. 6, pp. 5441-5455, June 2024.
  • S. Ma, C. Zhhang, B. Shen, Y. Wu, et al., Semantic Feature Division Multiple Access for Multi-user Digital Interference Networks, IEEE Trans. Wireless Commun., vol. 23, no. 10, pp. 15230-15244, Oct. 2024.
  • S. Ma, Z. Zhang, Y. Wu, et al., Features Disentangled Semantic Broadcast Communication Networks, IEEE Trans. Wireless Commun., vol. 23, no. 6, pp. 6580-6594, June 2024.
  • S. Ma, W. Qiao, Y. Wu, et al., Task-oriented Explainable Semantic Communications, IEEE Trans. Wireless Commun., vol. 22, no. 12, pp. 9248-9262, Jan. 2024.
  • S. Xie, S. Ma, M. Ding, M. Tang, Y. Shi, and Y. Wu, Robust Information Bottleneck for Task-oriented Communication with Digital Modulation, IEEE J. Sel. Areas Commun., vol. 41, no. 8, pp. 2577-2591, Aug. 2023.
  • Y. Shi, Y, Zhou, D. Wen, Y. Wu, C. Jiang, and K. Letaief, Task-oriented Communications for 6G: Vision, Principles, and Technologies, IEEE Wireless Communications Magazine, vol. 30, no. 3, pp. 78-85, June, 2023.
  • S. Ma, J. Wang, C. Du, H. Li, Y. Wu, C. Shen, N. Al-Dhahir, and S. Li, Joint Beamforming and PD Orientation Design for Mobile Visible Light Communications, IEEE Trans. Wireless Commun., vol. 22, no. 8, pp. 5056-5069, Aug. 2023.
  • S. Ma, S. Cao, H. Li, S. Lu, T. Yang, Y. Wu, N. Al-Dhahir, and S. Li, Waveform Design and Optimization for Integrated Visible Light Positioning and Communication, IEEE Trans. Commun., vol. 71, no. 9, pp. 5392-5407, July, 2023.
  • S. Ma, R. Yang, C. Du, H. Li, Y. Wu, N. Al-Dhahir, and S. Li, Robust Power Allocation for Integrated Visible Light Positioning and Communication Networks, IEEE Trans. Commun., vol. 71, no. 8, pp. 4764-4777, Aug. 2023.
  • S. Ma, H. Sheng, R. Yang, H. Li, Y. Wu, C. Shen, M, Safari, S. Li, Covert Beamforming Design for Integrated Radar Sensing and Communication Systems, IEEE Trans. Wireless Commun., vol. 22, no. 1, pp. 718-731, Jan. 2023.
  • Y. Yang, Y. Zhou, Y. Wu, and Y. Shi, Differentially Private Federated Learning via Reconfigurable Intelligent Surface, IEEE Internet of Things Journal, vol. 9, no. 20, pp. 19728-19743, 15 Oct.15, 2022.
  • S. Ma, Y. Chen, H. Li, B. Li, Y. Wu, M, Safari, S. Li, N. Al-Dhahir, Optimal Power Allocation for Integrated Visible Light Positioning and Communication System with a Single LEDLamp, IEEE Trans. Commun., vol. 70, no. 10, pp. 6734-6747, Oct. 2022.
  • S. Ma, Y. Zhang, H. Li, Jia Shi, L. Yang, Y. Wu, N. Al-Dhahir, and S. Li, Optimal Probabilistic Constellation Shaping for Covert Communications, IEEE Transactions on Information Forensics & Security, vol. 17, pp. 3165-3178, Aug. 2022.
  • Y. Ma, Y. Wu, and C. Liu, A graph-based author name disambiguation method and analysis via information theory, Entropy, vol. 22, no. 4, pp. 416, April 2020.

    • Conference Papers:
  • H. Yang, Y. Wu, D. Wen, Y. Zhou, and Y. Shi, Structured IB: Improving Information Bottleneck with Structured Feature Learning, accepted, AAAI 2025.
  • S. Xie, Y. Wu, K. Liao, L. Chen, C. Liu, H. Shen, M. Tang, and Lu Sun, Fed-SC: One-Shot Federated Subspace Clustering over High-Dimensional Data, in IEEE International Conference on Data Engineering (ICDE), July 2023.
  • Y. Yang, Y. Wu, S. Ma, and Y. Shi, Multi-Task-Oriented Broadcast for Edge AI Inference via Information Bottleneck, in IEEE Global Communications Conference (Globecom), 2023.
  • L.Xing, X. Jia, T. Wang, Y. Wu, and Y. Shi, Blind Demixing for Federated Edge Learning, in IEEE International Mediterranean Conference on Communications and Networking (MeditCom), 2023.
  • J. Zhu, Y. Shi, M. Fu, Y. Zhou, Y. Wu, L. Fu, Latency Minimization for Wireless Federated Learning with Heterogeneous Local Updates, in IEEE WCNC, 2023.
  • J. Li, Y. Shi, Y. Wu, Reconfigurable Intelligent Surface Assisted Over-the-Air Computation in Multi-Cell Networks, in 2022 IEEE International Mediterranean Conference on Communications and Networking (MeditCom) , Athens, Greece, 2022, pp. 43-48.
  • X. Zeng, L. Xing, Y. Wu, and Y. Shi, Beamforming Design for Integrated Sensing and SWIPT System, in IEEE 33rd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC) , Kyoto, Japan, 2022, pp. 403-408.
  • X. Zeng, S. Xia, K. Yang, Y. Wu, and Y. Shi, Over-the-Air Computation for Vertical Federated Learning, in IEEE International Conference on Communications Workshop (ICC workshop), Seoul, Korea, Republic of, 2022, pp. 788-793.
  • Z. Yang, Y. Zhou, Y. Wu, and Y. Shi, Communication-efficient quantized SGD for learning polynomial neural network, IEEE 40th International Performance Computing and Communications Conference (IPCCC) Workshop, 2021

    • Communication for Distributed Caching and Computing

    Journal Papers:
  • Y. Wang and Y. Wu, Coded Distributed Computing with Pre-set Data Placement and Output Functions Assignment, IEEE Trans. Inf. Theory, vol. 71, no. 3, pp. 2195-2217, March 2025.
  • Y. Wu, X. Song, K. Wang, S. Cao, J. Chen, and S. Ma, Communication-Efficient Centralized and Decentralized Coded Caching for Hierarchical Cache-Aided Networks, IEEE Transactions on Cognitive Communications and Networking, Early Acces, 2025.
  • K. Liang, S. Li, M. Ding, F. Tian, and Y. Wu, Privacy-Preserving Coded Schemes for Multi-Server Federated Learning with Straggling Links, IEEE Transactions on Information Forensics & Security, vol. 20, pp. 1222-1236, 2024.
  • Y. Wu, C. Li, Y. Hu, X. Song, S. Ma, and Y. Shi, Coded Computing for Multi-cluster Distributed Computations, IEEE Trans. Commun., vol. 73, no. 2, pp. 1114-1127, Feb. 2025.
  • Z. Huang, K. Yuan, S. Ma, Y. Bi, and Y. Wu, Coded Computing for Half-Duplex Wireless Distributed Computing Systems via Interference Alignment, IEEE Trans. Wireless Commun., vol. 23, no. 11, pp. 17399-17414, Nov. 2024.
  • H. Hu, S. Li, M. Cheng, S. Ma, Y. Shi, and Y. Wu, On Exploiting Network Topology for Hierarchical Coded Multi-task Learning, IEEE Trans. Commun., vol. 72, no. 8, pp. 4930-4944, Aug. 2024.
  • M. Cheng, Y. Xie, Z. Huang, M. Zhang, and Y. Wu, Caching Scheme for Partially Connected Linear Networks Via Multi-antenna Placement Delivery Array, IEEE Trans. Commun., vol. 72, no. 12, pp. 7715-7726, Dec. 2024.
  • M. Cheng, Y. Wu, X. Li, and D. Wu, Asymptotically Optimal Coded Distributed Computing via Combinatorial Designs, IEEE/ACM Trans. Netw., vol. 32, no. 4, pp. 3018 - 3033, Aug. 2024.
  • L. Zhang, Y. Kong, Y. Wu, and M. Cheng, Hierarchical Cache-Aided Networks for Linear Function Retrieval, Entropy, Feb. 2024.
  • M. Zhang, M. Chen, Y. Wu, and X. Li, Coded Caching for Dense-user Combination Networks in Binary Field, IEEE Trans. Commun., vol. 72, no. 5, pp. 2716-2730, May. 2024
  • M. Cheng, J. Xu, M. Zhang, and Y. Wu, Coded Caching Schemes for Two-dimensional Caching-aided Ultra-dense Networks, IEEE Trans. Commun., vol. 71, no. 10, pp. 5698-5712, July, 2023.
  • H. Hu, Y. Wu, Y. Shi, S. Li, and W. Zhang, Communication-Efficient Coded Computing for Distributed Multi-task Learning, IEEE Trans. Commun., vol. 71, no. 7, pp. 3861-3875, May 2023.
  • H. Cheng, J. Long, S. Ma, M. Tang, Y. Wu, On the Optimality of Data Exchange for Master-Aided Edge Computing Systems, IEEE Trans. Commun., vol. 71, no. 3, pp. 1364--1376, Jan. 2023.
  • H. Tu, K. Yuan, S. Ma, and Y. Wu, Implementation of parallel map and shuffle phases for coded distributed computing, IEEE Communications Letters, vol. 26, no. 2, pp. 282-285, Feb. 2022.
  • Z. Huang, J. Chen, X. You, S. Ma, and Y. Wu. Coded Caching for Broadcast Networks with User Cooperation, Entropy, vol 24, no. 8, pp. 1034, July, 2022.

    • Conference Papers:
  • H. Chen, M. Cheng, and Y. Wu, On Decentralized Linearly Separable Computation With the Minimum Computation Cost, in IEEE Int. Symp. Information Theory (ISIT), July, 2024.
  • K. Liang, S. Li, M. Ding, and Y. Wu, Multi-Server Secure Aggregation with Unreliable Communication Links, in IEEE Global Communications Conference (Globecom), 2023.
  • H. Zhong, K. Liang, and Y. Wu, Lempel-Ziv Coding for Federated Learning, in IEEE Globecom Workshops (GC Wkshps), Kuala Lumpur, Malaysia, 2023
  • Z. Huang, S. Li, K. Liang, and Y. Wu, Secure Gradient Aggregation for Wireless Multi-server Federated Learning, in IEEE Int. Symp. Information Theory (ISIT), 2023.
  • M. Cheng, J. Xu, Y. Wu, and M. Zhang, Coded Caching Scheme for Two-dimensional Caching- Aided Ultra-dense Networks, in IEEE Int. Symp. Information Theory (ISIT), 2023.
  • H. Hu, Y. Wu, S. Li, and M. Cheng, Coded Distributed Computing for Hierarchical Multi-Task Learning, in IEEE Information Theory Workshop (ITW), 2023.
  • Y. Kong, Y. Wu, M. Cheng, Combinatorial Designs for Coded Caching on Hierarchical Networks, in IEEE Wireless Communications & Networking Conference (WCNC), 2023.
  • K. Yuan and Y. Wu, Coded Wireless Distributed Computing via Interference Alignment, in IEEE Int. Symp. Information Theory (ISIT), Espoo, Finland, 2022.
  • C. Pang and Y. Wu, Distributed Computing for Hierarchical MapReduce Systems, in International Conference on Computer and Communication Systems (ICCCS), Guangzhou, China, 2023
  • Y. Wang and Y. Wu, Coded MapReduce with Pre-set Data and Reduce Function Assignments, in IEEE Global Communications Conference (Globecom), Rio de Janeiro, Brazil, 2022.
  • M. Cheng and Y. Wu, Lower Bound on Load of Coded Caching Schemes for Finite Subpacketizations , in International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks (WiOpt) , Torino, Italy, 2022.
  • H. Tu, Q. Zai, C. Li, and Y. Wu, Efficient Coded Distributed Computing via Joint Cellular and D2D Communications, in IEEE International Conference on Communications (ICC), Seoul, South Korea, 2022.
  • H. Tang, H. Hu, K. Yuan. and Y. Wu, Communication-Efficient Coded Distributed Multi-Task Learning, in IEEE Global Communications Conference (Globecom), 2021.
  • S. -J. Cao, L. Yi, H. Chen, and Y. Wu, Coded Distributed Computation with Limited Resources, in IEEE Global Communications Conference (Globecom), 2021.
  • K. Liang and Y. Wu, Improved communication efficiency for distributed mean estimation with side information, in IEEE Int. Symp. Information Theory (ISIT), 2021.
  • L. Yi, S. Cao, and Y. Wu, Coding schemes and resource allocations for the multi-task coded distributed computation, ICC 2020 Workshop, 2021
  • K. Liang and Y. Wu, Two-layer coded gradient aggregation with straggling communication links, in IEEE Information Theory Workshop (ITW), 2021
  • S. Cao, J. Chen, Y. Wu, and K. Wang, Coded caching for relay networks: the impact of caching memories, in Information Theory Workshop (ITW), 2021
  • H. Chen and Y. Wu, Coded computing for master-aided distributed computing systems, IEEE Information Theory Workshop (ITW), accepted, 2021
  • X. You, Y. Wu, and J. Chen, Cache-aided broadcast channels with user cooperation, in Allerton Conference on Communication, Control, and Computing (Allerton), Monticello, IL, USA, 2019.
  • J. Chen, H. Yin, X. You, Y. Geng, and Y. Wu, Centralized coded caching with user cooperation, 2019 IEEE Information Theory Workshop (ITW), Visby, Sweden, 2019.
  • K. Wang, Y. Wu, J. Chen, and H. Yin, Reduce transmission delay for caching-aided two-layer networks, 2019 IEEE International Symposium on Information Theory (ISIT), Paris, France, 2019.

    • Network Information Theory

    Journal Papers:
  • R. Tang, S. Xie, and Y. Wu. On the achievable rate region of the K-receiver broadcast channels via exhaustive message splitting, Entropy, vol. 23, no. 11, pp. 1408, Oct. 2021.
  • B. Hu, K. Wang, Y. Ma, and Y. Wu, On the capacity regions of degraded relay broadcast channels with and without feedback, Entropy, vol. 22, no. 7, pp. 784, July 2020.
  • Y. Wu, Achievable rates for discrete memoryless multicast networks with and without feedback, IEEE Trans. Inf. Theory, vol. 64, no. 4, pp. 2321-2332, Jan., 2018.
  • Y. Wu and M. Wigger, Coding schemes with rate-limited feedback that improve over the nofeedback capacity for a large class of broadcast channels, IEEE Trans. Inf. Theory,vol. 62, no. 4, pp. 2009-2033, April, 2016.
  • Y. Wu, P. Minero, and M. Wigger, Insufficiency of linear-feedback schemes in Gaussian broadcast channels with common message, IEEE Trans. Inf. Theory., vol. 60, no. 8, pp. 4553-4566, August 2014.

    • Conference Papers:
  • K. Wang, Y. Wu, and Y. Ma, Capacity region of degraded relay broadcast channel, in IEEE Int. Symp. Information Theory (ISIT), pp. 1405-1409, July, 2018.
  • Y. Wu, Achievable rate regions for cooperative relay broadcast channels with rate-limited feedback, IEEE Int. Symp. Information Theory (ISIT), pp. 1660-1664, July, 2016.
  • Y. Wu, Coding schemes for discrete memoryless multicast networks with rate-limited feedback, in IEEE Information Theory Workshop (ITW) 2015 IEEE, pp. 197-201, Oct. 2015.
  • Y. Wu, Coding schemes for discrete memoryless multicast networks with and without feedback, in 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton), pp. 514-521, Oct. 2015
  • Y. Wu, Coding schemes for the discrete memoryless broadcast channel with feedback, 17th Joint Conference on Communications and Coding (JCCC), March 2015.
  • Y. Wu and M. Wigger, Coding schemes for the discrete memoryless broadcast channel with rate-limited feedback, in IEEE Int. Symp. Information Theory, pp. 2127-2131, July, 2014.
  • Y. Wu and M. Wigger, Any positive feedback rate increases the capacity of strictly less-noisy broadcast channels, in IEEE Information Theory Workshop (ITW), pp. 579-583, Sept 2013.
  • Y. Wu, P. Minero, and M. Wigger, Reliability of the Gaussian broadcast channel with common message and feedback, in Signal Processing Advances in Wireless Communications IEEE 14th Workshop on, pp. 210-214, June, 2013. (Invited paper)