On spectral distribution of kernel matrices related to radial basis functions AJ Wathen, S Zhu Numerical Algorithms 70 (4), 709-726, 2015 | 49 | 2015 |
Unleashing the potential of prompt engineering in large language models: a comprehensive review B Chen, Z Zhang, N Langrené, S Zhu arXiv preprint arXiv:2310.14735, 2023 | 28 | 2023 |
Compactly supported radial basis functions: how and why? S Zhu OCCAM report, 2012 | 22 | 2012 |
Knowledge discovery and recommendation with linear mixed model Z Chen, S Zhu, Q Niu, T Zuo Ieee Access 8, 38304-38317, 2020 | 20 | 2020 |
Minimizing synchronizations in sparse iterative solvers for distributed supercomputers SX Zhu, TX Gu, XP Liu Computers & Mathematics With Applications 67 (1), 199-209, 2014 | 20 | 2014 |
Convexity and solvability for compactly supported radial basis functions with different shapes S Zhu, AJ Wathen Journal of Scientific Computing 63 (3), 862-884, 2015 | 18 | 2015 |
Information splitting for big data analytics S Zhu, T Gu, X Xu, Z Mo IEEE CyberC2016, 2016 | 16 | 2016 |
Essential formulae for restricted maximum likelihood and its derivatives associated with the linear mixed models S Zhu, AJ Wathen arXiv preprint arXiv:1805.05188, 2018 | 13 | 2018 |
Learning with linear mixed model for group recommendation systems B Gao, G Zhan, H Wang, Y Wang, S Zhu Proceedings of the 2019 11th International Conference on Machine Learning …, 2019 | 12 | 2019 |
Fast calculation of restricted maximum likelihood methods for unstructured high-throughput data S Zhu 2017 IEEE 2nd international conference on big data analysis, 2017 | 10 | 2017 |
AIMS: Average information matrix splitting S Zhu, T Gu, X Liu Mathematical Foundations of Computing (MFC), 2016 | 10* | 2016 |
Solving inverse eigenvalue problems via Householder and rank-one matrices S Zhu, T Gu, X Liu Linear algebra and its applications 430 (1), 318-334, 2009 | 10 | 2009 |
Sparse inversion for derivative of log determinant S Zhu, AJ Wathen arXiv:1911.00685 1 (arXiv:1911.00685), arXiv:1911.00685, 2019 | 9* | 2019 |
A hybrid recommender system combing singular value decomposition and linear mixed model T Zuo, S Zhu, J Lu Intelligent Computing. SAI 2020. 1228, 347-362, 2020 | 7 | 2020 |
Censorious Young: Knowledge Discovery from High-throughput Movie Rating Data with LME4 Z Chen, S Zhu, Q Niu, X Lu ICBDA, 32-36, 2019 | 6 | 2019 |
Big data, fast models: faster calculation of models from high-throughput biological data sets S Welham, S Zhu, AJ Wathen Smith Industry Mathematics Institute, The University of Oxford, Oxford …, 2013 | 6 | 2013 |
Generalized rough polyharmonic splines for multiscale pdes with rough coefficients X Liu, L Zhang, S Zhu arXiv preprint arXiv:2103.01788, 2021 | 5 | 2021 |
On The Memory Wall And Performance Of Symmetric Sparse Matrix Vector Multiplications In Different Data Structures On Shared Memory Machines T Gu, X Liu, Z Mo, X Xu, S Zhu IEEE UIC-ATC-ScalCom-CBDCom-IoP, 1439-1444, 2015 | 5 | 2015 |
Personalized Recommender Systems with Multi-source Data YI Wang, T Wu, M Fei, S Zhu SAI 2020: Intelligent Computing 1228, 219-233, 2020 | 4 | 2020 |
Modeling the Cashflow Management of Bike Sharing Industry B Shen, Y Shan, Y Jia, D Xie, S Zhu Lecture Notes in Business Information Processing 354, 132-146, 2019 | 4 | 2019 |