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Wentai Wu
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2020 – today
- 2025
- [j27]Zhetao Li, Xiyu Zeng, Yong Xiao, Chengxin Li, Wentai Wu, Haolin Liu:
Pattern-Sensitive Local Differential Privacy for Finite-Range Time-Series Data in Mobile Crowdsensing. IEEE Trans. Mob. Comput. 24(1): 1-14 (2025) - 2024
- [j26]Peng Peng, Weiwei Lin, Wentai Wu, Haotong Zhang, Shaoliang Peng, Qingbo Wu, Keqin Li:
A survey on computation offloading in edge systems: From the perspective of deep reinforcement learning approaches. Comput. Sci. Rev. 53: 100656 (2024) - [j25]Tianyu He, Peiyi Han, Shaoming Duan, Zirui Wang, Wentai Wu, Chuanyi Liu, Jianrun Han:
Generative data augmentation with differential privacy for non-IID problem in decentralized clinical machine learning. Future Gener. Comput. Syst. 160: 171-184 (2024) - [j24]Jianpeng Lin, Weiwei Lin, Wentai Wu, Wenjun Lin, Keqin Li:
Energy-aware virtual machine placement based on a holistic thermal model for cloud data centers. Future Gener. Comput. Syst. 161: 302-314 (2024) - [j23]Weiwei Lin, Songbo Wang, Wentai Wu, Dongdong Li, Albert Y. Zomaya:
HybridAD: A Hybrid Model-Driven Anomaly Detection Approach for Multivariate Time Series. IEEE Trans. Emerg. Top. Comput. Intell. 8(1): 866-878 (2024) - [c2]Shengsheng Lin, Weiwei Lin, Wentai Wu, Haojun Chen, Junjie Yang:
SparseTSF: Modeling Long-term Time Series Forecasting with *1k* Parameters. ICML 2024 - [i10]Shengsheng Lin, Weiwei Lin, Wentai Wu, Haojun Chen, Junjie Yang:
SparseTSF: Modeling Long-term Time Series Forecasting with 1k Parameters. CoRR abs/2405.00946 (2024) - [i9]Shengsheng Lin, Weiwei Lin, Xinyi Hu, Wentai Wu, Ruichao Mo, Haocheng Zhong:
CycleNet: Enhancing Time Series Forecasting through Modeling Periodic Patterns. CoRR abs/2409.18479 (2024) - 2023
- [j22]Weiwei Lin, Yufeng Zhang, Wentai Wu, Simon Fong, Ligang He, Jia Chang:
An adaptive workload-aware power consumption measuring method for servers in cloud data centers. Computing 105(3): 515-538 (2023) - [j21]Weiwei Lin, Chennian Xiong, Wentai Wu, Fang Shi, Keqin Li, Minxian Xu:
Performance Interference of Virtual Machines: A Survey. ACM Comput. Surv. 55(12): 254:1-254:37 (2023) - [j20]Wangbo Shen, Weiwei Lin, Yulei Wu, Fang Shi, Wentai Wu, Keqin Li:
Evolving Deep Multiple Kernel Learning Networks Through Genetic Algorithms. IEEE Trans. Ind. Informatics 19(2): 1569-1580 (2023) - [j19]Bo Liu, Rui Chen, Weiwei Lin, Wentai Wu, Jianpeng Lin, Keqin Li:
Thermal-aware virtual machine placement based on multi-objective optimization. J. Supercomput. 79(11): 12563-12590 (2023) - [j18]Bo Liu, Rui Chen, Weiwei Lin, Wentai Wu, Jianpeng Lin, Keqin Li:
Publisher Correction to: Thermal‑aware virtual machine placement based on multi‑objective optimization. J. Supercomput. 79(15): 17756-17757 (2023) - [j17]Wentai Wu, Ligang He, Weiwei Lin, Carsten Maple:
FedProf: Selective Federated Learning Based on Distributional Representation Profiling. IEEE Trans. Parallel Distributed Syst. 34(6): 1942-1953 (2023) - [i8]Shengsheng Lin, Weiwei Lin, Wentai Wu, Songbo Wang, Yongxiang Wang:
PETformer: Long-term Time Series Forecasting via Placeholder-enhanced Transformer. CoRR abs/2308.04791 (2023) - [i7]Shengsheng Lin, Weiwei Lin, Wentai Wu, Feiyu Zhao, Ruichao Mo, Haotong Zhang:
SegRNN: Segment Recurrent Neural Network for Long-Term Time Series Forecasting. CoRR abs/2308.11200 (2023) - 2022
- [j16]Fang Shi, Chunchao Hu, Weiwei Lin, Lisheng Fan, Tiansheng Huang, Wentai Wu:
VFedCS: Optimizing Client Selection for Volatile Federated Learning. IEEE Internet Things J. 9(24): 24995-25010 (2022) - [j15]Pengcheng Li, Zhangyu Li, Xiongwen Pang, Hui Wang, Weiwei Lin, Wentai Wu:
Multi-scale residual denoising GAN model for producing super-resolution CTA images. J. Ambient Intell. Humaniz. Comput. 13(3): 1515-1524 (2022) - [j14]Wentai Wu, Ligang He, Weiwei Lin, Yi Su, Yuhua Cui, Carsten Maple, Stephen A. Jarvis:
Developing an Unsupervised Real-Time Anomaly Detection Scheme for Time Series With Multi-Seasonality. IEEE Trans. Knowl. Data Eng. 34(9): 4147-4160 (2022) - [j13]Weiwei Lin, Wentai Wu, Ligang He:
An On-Line Virtual Machine Consolidation Strategy for Dual Improvement in Performance and Energy Conservation of Server Clusters in Cloud Data Centers. IEEE Trans. Serv. Comput. 15(2): 766-777 (2022) - 2021
- [b1]Wentai Wu:
Towards efficient horizontal federated learning. University of Warwick, Coventry, UK, 2021 - [j12]Weiwei Lin, Fang Shi, Wentai Wu, Keqin Li, Guangxin Wu, Al-Alas Mohammed:
A Taxonomy and Survey of Power Models and Power Modeling for Cloud Servers. ACM Comput. Surv. 53(5): 100:1-100:41 (2021) - [j11]Wentai Wu, Ligang He, Weiwei Lin, Rui Mao, Carsten Maple, Stephen A. Jarvis:
SAFA: A Semi-Asynchronous Protocol for Fast Federated Learning With Low Overhead. IEEE Trans. Computers 70(5): 655-668 (2021) - [j10]Wentai Wu, Weiwei Lin, Ligang He, Guangxin Wu, Ching-Hsien Hsu:
A Power Consumption Model for Cloud Servers Based on Elman Neural Network. IEEE Trans. Cloud Comput. 9(4): 1268-1277 (2021) - [j9]Wentai Wu, Ligang He, Weiwei Lin, Rui Mao:
Accelerating Federated Learning Over Reliability-Agnostic Clients in Mobile Edge Computing Systems. IEEE Trans. Parallel Distributed Syst. 32(7): 1539-1551 (2021) - [j8]Tiansheng Huang, Weiwei Lin, Wentai Wu, Ligang He, Keqin Li, Albert Y. Zomaya:
An Efficiency-Boosting Client Selection Scheme for Federated Learning With Fairness Guarantee. IEEE Trans. Parallel Distributed Syst. 32(7): 1552-1564 (2021) - [c1]Hao Wu, Ligang He, Chang-Tsun Li, Junyu Li, Wentai Wu, Carsten Maple:
MGGAN: Improving sample generations of Generative Adversarial Networks. HPCC/DSS/SmartCity/DependSys 2021: 369-376 - [i6]Wentai Wu, Ligang He, Weiwei Lin, Rui Mao, Chenlin Huang, Wei Song:
FedProf: Optimizing Federated Learning with Dynamic Data Profiling. CoRR abs/2102.01733 (2021) - [i5]Wentai Wu, Ligang He, Weiwei Lin:
Variation-Incentive Loss Re-weighting for Regression Analysis on Biased Data. CoRR abs/2109.06565 (2021) - 2020
- [j7]Xiong Wen Pang, Yanqiang Zhou, Pengcheng Li, Weiwei Lin, Wentai Wu, James Z. Wang:
A novel syntax-aware automatic graphics code generation with attention-based deep neural network. J. Netw. Comput. Appl. 161: 102636 (2020) - [i4]Wentai Wu, Ligang He, Weiwei Lin, Rui Mao:
Accelerating Federated Learning over Reliability-Agnostic Clients in Mobile Edge Computing Systems. CoRR abs/2007.14374 (2020) - [i3]Tiansheng Huang, Weiwei Lin, Wentai Wu, Ligang He, Keqin Li, Albert Y. Zomaya:
An Efficiency-boosting Client Selection Scheme for Federated Learning with Fairness Guarantee. CoRR abs/2011.01783 (2020)
2010 – 2019
- 2019
- [i2]Wentai Wu, Ligang He, Weiwei Lin:
Local Trend Inconsistency: A Prediction-driven Approach to Unsupervised Anomaly Detection in Multi-seasonal Time Series. CoRR abs/1908.01146 (2019) - [i1]Wentai Wu, Ligang He, Weiwei Lin, Rui Mao, Stephen A. Jarvis:
SAFA: a Semi-Asynchronous Protocol for Fast Federated Learning with Low Overhead. CoRR abs/1910.01355 (2019) - 2018
- [j6]Weiwei Lin, Wentai Wu, Haoyu Wang, James Z. Wang, Ching-Hsien Hsu:
Experimental and quantitative analysis of server power model for cloud data centers. Future Gener. Comput. Syst. 86: 940-950 (2018) - [j5]Wentai Wu, Weiwei Lin, Ching-Hsien Hsu, Ligang He:
Energy-efficient hadoop for big data analytics and computing: A systematic review and research insights. Future Gener. Comput. Syst. 86: 1351-1367 (2018) - [j4]Weiwei Lin, Haoyu Wang, Wentai Wu:
A Power Monitoring System Based on a Multi-Component Power Model. Int. J. Grid High Perform. Comput. 10(1): 16-30 (2018) - [j3]Weiwei Lin, Weiqi Wang, Wentai Wu, Xiong Wen Pang, Bo Liu, Ying Zhang:
A heuristic task scheduling algorithm based on server power efficiency model in cloud environments. Sustain. Comput. Informatics Syst. 20: 56-65 (2018) - 2017
- [j2]Wentai Wu, Weiwei Lin, Zhiping Peng:
An intelligent power consumption model for virtual machines under CPU-intensive workload in cloud environment. Soft Comput. 21(19): 5755-5764 (2017) - 2016
- [j1]Weiwei Lin, Wentai Wu, James Z. Wang:
A Heuristic Task Scheduling Algorithm for Heterogeneous Virtual Clusters. Sci. Program. 2016: 7040276:1-7040276:10 (2016)
Coauthor Index
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