A Heuristic Task Scheduling Algorithm for Heterogeneous Virtual Clusters. - Weiwei Lin 001; Wentai Wu; James Z. Wang 002 (Sci. Program., 2016)

An intelligent power consumption model for virtual machines under CPU-intensive workload in cloud environment. - Wentai Wu; Weiwei Lin 001; Zhiping Peng (Soft Comput., 2017)

Experimental and quantitative analysis of server power model for cloud data centers. - Weiwei Lin 001; Wentai Wu; Haoyu Wang; James Z. Wang 002; Ching-Hsien Hsu (Future Gener. Comput. Syst., 2018)

Energy-efficient hadoop for big data analytics and computing: A systematic review and research insights. - Wentai Wu; Weiwei Lin 001; Ching-Hsien Hsu; Ligang He (Future Gener. Comput. Syst., 2018)

A Power Monitoring System Based on a Multi-Component Power Model. - Weiwei Lin 001; Haoyu Wang; Wentai Wu (Int. J. Grid High Perform. Comput., 2018)

A heuristic task scheduling algorithm based on server power efficiency model in cloud environments. - Weiwei Lin 001; Weiqi Wang; Wentai Wu; Xiong Wen Pang; Bo Liu 045; Ying Zhang (Sustain. Comput. Informatics Syst., 2018)

Local Trend Inconsistency: A Prediction-driven Approach to Unsupervised Anomaly Detection in Multi-seasonal Time Series. - Wentai Wu; Ligang He; Weiwei Lin 001 (CoRR, 2019)

SAFA: a Semi-Asynchronous Protocol for Fast Federated Learning with Low Overhead. - Wentai Wu; Ligang He; Weiwei Lin 001; Rui Mao 001; Stephen A. Jarvis (CoRR, 2019)

A novel syntax-aware automatic graphics code generation with attention-based deep neural network. - Xiong Wen Pang; Yanqiang Zhou; Pengcheng Li; Weiwei Lin 001; Wentai Wu; James Z. Wang 002 (J. Netw. Comput. Appl., 2020)

MGGAN: Improving sample generations of Generative Adversarial Networks. - Hao Wu 058; Ligang He; Chang-Tsun Li; Junyu Li; Wentai Wu; Carsten Maple (HPCC/DSS/SmartCity/DependSys, 2021)

FedProf: Optimizing Federated Learning with Dynamic Data Profiling. - Wentai Wu; Ligang He; Weiwei Lin 001; Rui Mao 001; Chenlin Huang; Wei Song (CoRR, 2021)

Variation-Incentive Loss Re-weighting for Regression Analysis on Biased Data. - Wentai Wu; Ligang He; Weiwei Lin 001 (CoRR, 2021)

A Taxonomy and Survey of Power Models and Power Modeling for Cloud Servers. - Weiwei Lin 001; Fang Shi; Wentai Wu; Keqin Li 001; Guangxin Wu; Al-Alas Mohammed (ACM Comput. Surv., 2021)

SAFA: A Semi-Asynchronous Protocol for Fast Federated Learning With Low Overhead. - Wentai Wu; Ligang He; Weiwei Lin 001; Rui Mao 001; Carsten Maple; Stephen A. Jarvis (IEEE Trans. Computers, 2021)

A Power Consumption Model for Cloud Servers Based on Elman Neural Network. - Wentai Wu; Weiwei Lin 001; Ligang He; Guangxin Wu; Ching-Hsien Hsu (IEEE Trans. Cloud Comput., 2021)

An Efficiency-Boosting Client Selection Scheme for Federated Learning With Fairness Guarantee. - Tiansheng Huang; Weiwei Lin 001; Wentai Wu; Ligang He; Keqin Li 001; Albert Y. Zomaya (IEEE Trans. Parallel Distributed Syst., 2021)

Accelerating Federated Learning Over Reliability-Agnostic Clients in Mobile Edge Computing Systems. - Wentai Wu; Ligang He; Weiwei Lin 001; Rui Mao 001 (IEEE Trans. Parallel Distributed Syst., 2021)

Towards efficient horizontal federated learning. - Wentai Wu (2021)

VFedCS: Optimizing Client Selection for Volatile Federated Learning. - Fang Shi; Chunchao Hu; Weiwei Lin 001; Lisheng Fan; Tiansheng Huang; Wentai Wu (IEEE Internet Things J., 2022)

Multi-scale residual denoising GAN model for producing super-resolution CTA images. - Pengcheng Li; Zhangyu Li; Xiongwen Pang; Hui Wang; Weiwei Lin 001; Wentai Wu (J. Ambient Intell. Humaniz. Comput., 2022)

Developing an Unsupervised Real-Time Anomaly Detection Scheme for Time Series With Multi-Seasonality. - Wentai Wu; Ligang He; Weiwei Lin 001; Yi Su; Yuhua Cui; Carsten Maple; Stephen A. Jarvis (IEEE Trans. Knowl. Data Eng., 2022)

An On-Line Virtual Machine Consolidation Strategy for Dual Improvement in Performance and Energy Conservation of Server Clusters in Cloud Data Centers. - Weiwei Lin 001; Wentai Wu; Ligang He (IEEE Trans. Serv. Comput., 2022)

SegRNN: Segment Recurrent Neural Network for Long-Term Time Series Forecasting. - Shengsheng Lin; Weiwei Lin 001; Wentai Wu; Feiyu Zhao; Ruichao Mo; Haotong Zhang 003 (CoRR, 2023)

Evolving Deep Multiple Kernel Learning Networks Through Genetic Algorithms. - Wangbo Shen; Weiwei Lin 001; Yulei Wu; Fang Shi; Wentai Wu; Keqin Li 001 (IEEE Trans. Ind. Informatics, 2023)

Thermal-aware virtual machine placement based on multi-objective optimization. - Bo Liu 045; Rui Chen; Weiwei Lin 001; Wentai Wu; Jianpeng Lin; Keqin Li 001 (J. Supercomput., 2023)

An adaptive workload-aware power consumption measuring method for servers in cloud data centers. - Weiwei Lin 001; Yufeng Zhang; Wentai Wu; Simon Fong 001; Ligang He; Jia Chang (Computing, 2023)

FedProf: Selective Federated Learning Based on Distributional Representation Profiling. - Wentai Wu; Ligang He; Weiwei Lin 001; Carsten Maple (IEEE Trans. Parallel Distributed Syst., 2023)

Publisher Correction to: Thermal‑aware virtual machine placement based on multi‑objective optimization. - Bo Liu 045; Rui Chen; Weiwei Lin 001; Wentai Wu; Jianpeng Lin; Keqin Li 001 (J. Supercomput., 2023)

Performance Interference of Virtual Machines: A Survey. - Weiwei Lin 001; Chennian Xiong; Wentai Wu; Fang Shi; Keqin Li 001; Minxian Xu (ACM Comput. Surv., 2023)

SparseTSF: Modeling Long-term Time Series Forecasting with *1k* Parameters. - Shengsheng Lin; Weiwei Lin 001; Wentai Wu; Haojun Chen; Junjie Yang (ICML, 2024)

CycleNet: Enhancing Time Series Forecasting through Modeling Periodic Patterns. - Shengsheng Lin; Weiwei Lin 001; Xinyi Hu; Wentai Wu; Ruichao Mo; Haocheng Zhong (NeurIPS, 2024)

A survey on computation offloading in edge systems: From the perspective of deep reinforcement learning approaches. - Peng Peng 005; Weiwei Lin 001; Wentai Wu; Haotong Zhang 003; Shaoliang Peng; Qingbo Wu 003; Keqin Li 001 (Comput. Sci. Rev., 2024)

Generative data augmentation with differential privacy for non-IID problem in decentralized clinical machine learning. - Tianyu He; Peiyi Han; Shaoming Duan; Zirui Wang; Wentai Wu; Chuanyi Liu; Jianrun Han (Future Gener. Comput. Syst., 2024)

Energy-aware virtual machine placement based on a holistic thermal model for cloud data centers. - Jianpeng Lin; Weiwei Lin 001; Wentai Wu; Wenjun Lin; Keqin Li 001 (Future Gener. Comput. Syst., 2024)

HybridAD: A Hybrid Model-Driven Anomaly Detection Approach for Multivariate Time Series. - Weiwei Lin 001; Songbo Wang; Wentai Wu; Dongdong Li; Albert Y. Zomaya (IEEE Trans. Emerg. Top. Comput. Intell., 2024)

Reliable Task Offloading in Sustainable Edge Computing with Imperfect Channel State Information. - Peng Peng 005; Wentai Wu; Weiwei Lin 001; Fan Zhang 112; Yongheng Liu; Keqin Li 001 (IEEE Trans. Netw. Serv. Manag., 2024)

Pattern-Sensitive Local Differential Privacy for Finite-Range Time-Series Data in Mobile Crowdsensing. - Zhetao Li; Xiyu Zeng; Yong Xiao; Chengxin Li; Wentai Wu; Haolin Liu (IEEE Trans. Mob. Comput., 2025)

Knowledge Augmentation in Federation: Rethinking What Collaborative Learning Can Bring Back to Decentralized Data. - Wentai Wu; Ligang He; Saiqin Long; Ahmed M. Abdelmoniem; Yingliang Wu; Rui Mao 001 (CoRR, 2025)

PETformer: Long-Term Time Series Forecasting via Placeholder-Enhanced Transformer. - Shengsheng Lin; Weiwei Lin 001; Wentai Wu; Songbo Wang; Yongxiang Wang (IEEE Trans. Emerg. Top. Comput. Intell., 2025)

Reinforcement learning-based task scheduling for heterogeneous computing in end-edge-cloud environment. - Wangbo Shen; Weiwei Lin 001; Wentai Wu; Haijie Wu; Keqin Li 001 (Clust. Comput., 2025)

Cacomp: A Cloud-Assisted Collaborative Deep Learning Compiler Framework for DNN Tasks on Edge. - Weiwei Lin 001; Jinhui Lin; Haotong Zhang 003; Wentai Wu; Weizheng Wu; Zhetao Li; Keqin Li 001 (IEEE Trans. Computers, 2025)

On Efficiency, Fairness and Security in AI Accelerator Resource Sharing: A Survey. - Jiahua Huang; Weiwei Lin 001; Wentai Wu; Yang Wang 006; Haocheng Zhong; Xinhua Wang; Keqin Li 001 (ACM Comput. Surv., 2025)