| SAFA: A semi-asynchronous protocol for fast federated learning with low overhead W Wu, L He, W Lin, R Mao, C Maple, S Jarvis IEEE Transactions on Computers 70 (5), 655-668, 2021 | 375 | 2021 |
| An efficiency-boosting client selection scheme for federated learning with fairness guarantee T Huang, W Lin, W Wu, L He, K Li, AY Zomaya IEEE Transactions on Parallel and Distributed Systems 32 (7), 1552-1564, 2020 | 278 | 2020 |
| Accelerating federated learning over reliability-agnostic clients in mobile edge computing systems W Wu, L He, W Lin, R Mao IEEE Transactions on Parallel and Distributed Systems 32 (7), 1539-1551, 2021 | 116 | 2021 |
| Segrnn: Segment recurrent neural network for long-term time series forecasting S Lin, W Lin, W Wu, F Zhao, R Mo, H Zhang arXiv preprint arXiv:2308.11200, 2023 | 83 | 2023 |
| Energy-efficient hadoop for big data analytics and computing: A systematic review and research insights WT Wu, WW Lin, CH Hsu, LG He Future Generation Computer Systems 86, 1351-1367, 2018 | 78 | 2018 |
| Developing an unsupervised real-time anomaly detection scheme for time series with multi-seasonality W Wu, L He, W Lin, Y Su, Y Cui, C Maple, S Jarvis IEEE Transactions on Knowledge and Data Engineering 34 (9), 4147-4160, 2022 | 66 | 2022 |
| A taxonomy and survey of power models and power modeling for cloud servers W Lin, F Shi, W Wu, K Li, G Wu, AA Mohammed ACM Computing Surveys (CSUR) 53 (5), 1-41, 2020 | 60 | 2020 |
| An on-line virtual machine consolidation strategy for dual improvement in performance and energy conservation of server clusters in cloud data centers W Lin, W Wu, L He IEEE Transactions on Services Computing 15 (2), 766-777, 2022 | 55 | 2022 |
| Sparsetsf: Modeling long-term time series forecasting with 1k parameters S Lin, W Lin, W Wu, H Chen, J Yang arXiv preprint arXiv:2405.00946, 2024 | 47 | 2024 |
| Experimental and quantitative analysis of server power model for cloud data centers W Lin, W Wu, H Wang, JZ Wang, CH Hsu Future Generation Computer Systems 86, 940-950, 2018 | 43 | 2018 |
| A heuristic task scheduling algorithm based on server power efficiency model in cloud environments W Lin, W Wang, W Wu, X Pang, B Liu, Y Zhang Sustainable computing: informatics and systems 20, 56-65, 2018 | 42 | 2018 |
| An intelligent power consumption model for virtual machines under CPU-intensive workload in cloud environment W Wu, W Lin, Z Peng Soft Computing 21, 5755-5764, 2017 | 40 | 2017 |
| A power consumption model for cloud servers based on elman neural network W Wu, W Lin, L He, G Wu, CH Hsu IEEE Transactions on Cloud Computing 9 (4), 1268-1277, 2021 | 38 | 2021 |
| Performance interference of virtual machines: A survey W Lin, C Xiong, W Wu, F Shi, K Li, M Xu ACM Computing Surveys 55 (12), 1-37, 2023 | 28 | 2023 |
| Petformer: Long-term time series forecasting via placeholder-enhanced transformer S Lin, W Lin, W Wu, S Wang, Y Wang IEEE Transactions on Emerging Topics in Computational Intelligence, 2024 | 25 | 2024 |
| VFedCS: Optimizing client selection for volatile federated learning F Shi, C Hu, W Lin, L Fan, T Huang, W Wu IEEE Internet of Things Journal 9 (24), 24995-25010, 2022 | 25 | 2022 |
| A heuristic task scheduling algorithm for heterogeneous virtual clusters W Lin, W Wu, JZ Wang Scientific Programming 2016 (1), 7040276, 2016 | 22 | 2016 |
| A novel syntax-aware automatic graphics code generation with attention-based deep neural network X Pang, Y Zhou, P Li, weiwei Lin, W Wu, JZ Wang Journal of Network and Computer Applications, 0 | 20* | |
| Multi-scale residual denoising GAN model for producing super-resolution CTA images P Li, Z Li, X Pang, H Wang, W Lin, W Wu Journal of Ambient Intelligence and Humanized Computing, 1-10, 2022 | 15 | 2022 |
| FedProf: Selective federated learning based on distributional representation profiling W Wu, L He, W Lin, C Maple IEEE Transactions on Parallel and Distributed Systems 34 (6), 1942-1953, 2023 | 13 | 2023 |
Weiwei Lin(林伟伟), Professor, IEEE S...South China University of Technology; Pengcheng Laboratoryبريد إلكتروني تم التحقق منه على scut.edu.cn