| Large-scale and scalable latent factor analysis via distributed alternative stochastic gradient descent for recommender systems X Shi, Q He, X Luo, Y Bai, M Shang IEEE Transactions on Big Data 8 (2), 420-431, 2020 | 129 | 2020 |
| On minimizing total energy consumption in the scheduling of virtual machine reservations W Tian, M He, W Guo, W Huang, X Shi, M Shang, AN Toosi, R Buyya Journal of Network and Computer Applications 113, 64-74, 2018 | 55 | 2018 |
| Long-term performance of collaborative filtering based recommenders in temporally evolving systems X Shi, X Luo, M Shang, L Gu Neurocomputing 267, 635-643, 2017 | 43 | 2017 |
| SLAs-aware online task scheduling based on deep reinforcement learning method in cloud environment L Ran, X Shi, M Shang 2019 IEEE 21st International Conference on High Performance Computing and …, 2019 | 42 | 2019 |
| DCCR: Deep collaborative conjunctive recommender for rating prediction Q Wang, B Peng, X Shi, T Shang, M Shang IEEE Access 7, 60186-60198, 2019 | 37 | 2019 |
| Elastic-net regularized latent factor analysis-based models for recommender systems D Wang, Y Chen, J Guo, X Shi, C He, X Luo, H Yuan Neurocomputing 329, 66-74, 2019 | 20 | 2019 |
| Incremental Slope-one recommenders QX Wang, X Luo, Y Li, XY Shi, L Gu, MS Shang Neurocomputing 272, 606-618, 2018 | 19 | 2018 |
| PAPMSC: power-aware performance management approach for virtualized web servers via stochastic control X Shi, J Dong, SM Djouadi, Y Feng, X Ma, Y Wang Journal of Grid Computing 14, 171-191, 2016 | 17 | 2016 |
| Performance and cost-aware task scheduling via deep reinforcement learning in cloud environment Z Zhao, X Shi, M Shang International Conference on Service-Oriented Computing, 600-615, 2022 | 12 | 2022 |
| 一种基于并行化方法的自适应光学闭环预测控制器 史晓雨， 冯勇， 陈颖， 谭治英， 孙治， 李新阳 Acta Optica Sinica 32 (8), 801005--1, 2012 | 12 | 2012 |
| Long-term effects of user preference-oriented recommendation method on the evolution of online system X Shi, MS Shang, X Luo, A Khushnood, J Li Physica A: Statistical Mechanics and its Applications 467, 490-498, 2017 | 11 | 2017 |
| Relieving popularity bias in interactive recommendation: A diversity-novelty-aware reinforcement learning approach X Shi, Q Liu, H Xie, D Wu, B Peng, MS Shang, D Lian ACM Transactions on Information Systems 42 (2), 1-30, 2023 | 9 | 2023 |
| 自适应光学系统变形镜控制电压预测 史晓雨， 冯勇， 陈颖， 谭治英， 李新阳 强激光与粒子束 24 (6), 1281-1286, 2012 | 9 | 2012 |
| Power-aware performance management of virtualized enterprise servers via robust adaptive control X Shi, CA Briere, SM Djouadi, Y Wang, Y Feng Cluster Computing 18, 419-433, 2015 | 8 | 2015 |
| Random forest-based ensemble estimator for concrete compressive strength prediction via AdaBoost method Y Lv, X Shi, L Ran, M Shang Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery …, 2020 | 6 | 2020 |
| Aspect-aware Asymmetric Representation Learning Network for Review-based Recommendation H Liu, H Qiao, X Shi, M Shang 2022 International Joint Conference on Neural Networks (IJCNN), 1-8, 2022 | 5 | 2022 |
| A deep self-learning classification framework for incomplete medical patents with multi-label M Luo, X Shi, Q Ji, M Shang, X He, W Tao Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery …, 2020 | 5 | 2020 |
| A clustering-based collaborative filtering recommendation algorithm via deep learning user side information C Zhao, X Shi, M Shang, Y Fang Web Information Systems Engineering–WISE 2020: 21st International Conference …, 2020 | 5 | 2020 |
| seIMC: A GSW-based secure and efficient integer matrix computation scheme with implementation Y Bai, X Shi, W Wu, J Chen, Y Feng IEEE Access 8, 98383-98394, 2020 | 4 | 2020 |
| User heterogeneity and individualized recommender QX Wang, JJ Zhang, XY Shi, MS Shang Chinese Physics Letters 34 (6), 068902, 2017 | 4 | 2017 |
Ming-Sheng ShangChongqing Institute of Green and Intelligent Technology, Chinese Academy of SciencesEmail yang diverifikasi di cigit.ac.cn
