Personal profile
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
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SDG 7 Affordable and Clean Energy -
SDG 12 Responsible Consumption and Production
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Dive into the research topics where Xiaolu Wang is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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Achieving Linear Speedup in Asynchronous Federated Learning With Heterogeneous Clients
Wang, X., Li, Z., Jin, S. & Zhang, J., 2025, In: IEEE Transactions on Mobile Computing. 24, 1, p. 435-448 14 p.Research output: Contribution to journal › Article › peer-review
7 Link opens in a new tab Scopus citations -
EXPONENTIAL TOPOLOGY-ENABLED SCALABLE COMMUNICATION IN MULTI-AGENT REINFORCEMENT LEARNING
Li, X., Wang, X., Bai, C. & Zhang, J., 2025, 13th International Conference on Learning Representations, ICLR 2025. International Conference on Learning Representations, ICLR, p. 26014-26034 21 p. (13th International Conference on Learning Representations, ICLR 2025).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
2 Link opens in a new tab Scopus citations -
Momentum-Driven Adaptivity: Towards Tuning-Free Asynchronous Federated Learning
Yan, W., Zhong, X., Wang, X. & Zhang, Y. J. A., 2025, In: Proceedings of Machine Learning Research. 267, p. 70410-70441 32 p.Research output: Contribution to journal › Conference article › peer-review
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PROBLEM-PARAMETER-FREE FEDERATED LEARNING
Yan, W., Zhang, K., Wang, X. & Cao, X., 2025, 13th International Conference on Learning Representations, ICLR 2025. International Conference on Learning Representations, ICLR, p. 102639-102666 28 p. (13th International Conference on Learning Representations, ICLR 2025).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
4 Link opens in a new tab Scopus citations -
SAFL: Structure-Aware Personalized Federated Learning via Client-Specific Clustering and SCSI-Guided Model Pruning
Li, N., Wang, X., Du, X., Wang, C., Cai, P. & Wang, T., 2025, Proceedings of 2025 IEEE 31st International Conference on Parallel and Distributed Systems, ICPADS 2025. IEEE Computer Society, (Proceedings of the International Conference on Parallel and Distributed Systems - ICPADS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review