| A consensus-based global optimization method for high dimensional machine learning problems JA Carrillo, S Jin, L Li, Y Zhu ESAIM: Control, Optimisation and Calculus of Variations 27, S5, 2021 | 104 | 2021 |
| Hypocoercivity and Uniform Regularity for the Vlasov--Poisson--Fokker--Planck System with Uncertainty and Multiple Scales S Jin, Y Zhu SIAM Journal on Mathematical Analysis 50 (2), 1790-1816, 2018 | 52 | 2018 |
| The Vlasov--Poisson--Fokker--Planck system with uncertainty and a one-dimensional asymptotic preserving method Y Zhu, S Jin Multiscale Modeling & Simulation 15 (4), 1502-1529, 2017 | 46 | 2017 |
| Why resampling outperforms reweighting for correcting sampling bias with stochastic gradients J An, L Ying, Y Zhu arXiv preprint arXiv:2009.13447, 2020 | 33 | 2020 |
| Towards theoretical understanding of large batch training in stochastic gradient descent X Dai, Y Zhu arXiv preprint arXiv:1812.00542, 2018 | 11 | 2018 |
| FedCBO: reaching group consensus in clustered federated learning through consensus-based optimization JA Carrillo, NG Trillos, S Li, Y Zhu arXiv preprint arXiv:2305.02894, 2023 | 6 | 2023 |
| The Vlasov–Fokker–Planck equation with high dimensional parametric forcing term S Jin, Y Zhu, E Zuazua Numerische Mathematik 150 (2), 479-519, 2022 | 6 | 2022 |
| Optimal factor analysis and applications to content-based image retrieval Y Zhu, W Mio, X Liu Computer Vision and Computer Graphics. Theory and Applications …, 2008 | 6 | 2008 |
| Borrowing from the future: An attempt to address double sampling Y Zhu, L Ying Mathematical and scientific machine learning, 246-268, 2020 | 5 | 2020 |
| Borrowing from the future: Addressing double sampling in model-free control Y Zhu, Z Izzo, L Ying Mathematical and Scientific Machine Learning, 1099-1136, 2022 | 4 | 2022 |
| A note on optimization formulations of Markov decision processes L Ying, Y Zhu arXiv preprint arXiv:2012.09417, 2020 | 4 | 2020 |
| On Large Batch Training and Sharp Minima: A Fokker–Planck Perspective X Dai, Y Zhu Journal of Statistical Theory and Practice 14 (3), 1-31, 2020 | 4 | 2020 |
| A local sensitivity and regularity analysis for the Vlasov-Poisson-Fokker-Planck system with multi-dimensional uncertainty and the spectral convergence of the stochastic … Y Zhu Networks and Heterogeneous Media 14 (4), 677-707, 2019 | 3 | 2019 |
| Boundary Control of Vlasov--Fokker--Planck Equations M Herty, S Jin, Y Zhu arXiv preprint arXiv:2002.04215, 2020 | 2 | 2020 |
| An uncertainty quantification approach to the study of gene expression robustness P Degond, S Jin, Y Zhu arXiv preprint arXiv:1910.07188, 2019 | 2 | 2019 |
| Continuous-in-time Limit for Bayesian Bandits Y Zhu, Z Izzo, L Ying Journal of Machine Learning Research 24 (305), 1-35, 2023 | | 2023 |
| Variational actor-critic algorithms Y Zhu, L Ying ESAIM: Control, Optimisation and Calculus of Variations 29, 20, 2023 | | 2023 |
| Applications of Fokker Planck Equations in Machine Learning Algorithms Y Zhu Young Researchers Conference, 213-234, 2021 | | 2021 |
| Operator Shifting for Model-based Policy Evaluation X Tang, L Ying, Y Zhu arXiv preprint arXiv:2110.12658, 2021 | | 2021 |
| Operator Augmentation for Model-based Policy Evaluation. X Tang, L Ying, Y Zhu CoRR, 2021 | | 2021 |
Lexing YingProfessor of Mathematics, Stanford UniversityVerified email at stanford.edu
