| On the diffusion approximation of nonconvex stochastic gradient descent W Hu, CJ Li, L Li, JG Liu arXiv preprint arXiv:1705.07562, 2017 | 180* | 2017 |
| On the noisy gradient descent that generalizes as sgd J Wu, W Hu, H Xiong, J Huan, V Braverman, Z Zhu International Conference on Machine Learning, 10367-10376, 2020 | 122 | 2020 |
| Human mobility synchronization and trip purpose detection with mixture of hawkes processes P Wang, Y Fu, G Liu, W Hu, C Aggarwal Proceedings of the 23rd ACM SIGKDD international conference on knowledge …, 2017 | 91 | 2017 |
| Real-time frequency regulation using aggregated electric vehicles in smart grid MM Islam, X Zhong, Z Sun, H Xiong, W Hu Computers & Industrial Engineering 134, 11-26, 2019 | 45 | 2019 |
| Smoluchowski-Kramers approximation in the case of variable friction M Freidlin, W Hu arXiv preprint arXiv:1203.0603, 2012 | 40 | 2012 |
| Efficient smooth non-convex stochastic compositional optimization via stochastic recursive gradient descent W Hu, CJ Li, X Lian, J Liu, H Yuan Advances in Neural Information Processing Systems 32, 2019 | 36 | 2019 |
| On the fast convergence of random perturbations of the gradient flow J Yang, W Hu, CJ Li Asymptotic Analysis 122 (3-4), 371-393, 2021 | 23 | 2021 |
| Large deviations and averaging for systems of slow-fast stochastic reaction–diffusion equations W Hu, M Salins, K Spiliopoulos Stochastics and Partial Differential Equations: Analysis and Computations 7 …, 2019 | 22 | 2019 |
| Small mass asymptotic for the motion with vanishing friction M Freidlin, W Hu, A Wentzell Stochastic Processes and their Applications 123 (1), 45-75, 2013 | 20 | 2013 |
| Joint Control of Manufacturing and Onsite Microgrid System via Novel Neural-Network Integrated Reinforcement Learning Algorithms J Yang, Z Sun, W Hu, L Steimeister Applied Energy (accepted), 2022 | 18 | 2022 |
| Hypoelliptic multiscale Langevin diffusions: large deviations, invariant measures and small mass asymptotics W Hu, K Spiliopoulos | 17 | 2017 |
| On perturbations of generalized Landau-Lifshitz dynamics M Freidlin, W Hu Journal of Statistical Physics 144, 978-1008, 2011 | 16 | 2011 |
| Stochastic Recursive Momentum Method for Non-Convex Compositional Optimization H Yuan, W Hu arXiv preprint arXiv:2006.01688, 2020 | 13 | 2020 |
| Quasi-potential as an implicit regularizer for the loss function in the stochastic gradient descent W Hu, Z Zhu, H Xiong, J Huan arXiv preprint arXiv:1901.06054, 2019 | 12 | 2019 |
| On 2d incompressible Euler equations with partial damping T Elgindi, W Hu, V Sverak Communications in Mathematical Physics 355 (Issue 1, October 2017), pp. 145-159, 2015 | 10 | 2015 |
| On diffusion in narrow random channels M Freidlin, W Hu Journal of Statistical Physics 152, 136-158, 2013 | 10 | 2013 |
| Joint manufacturing and onsite microgrid system control using markov decision process and neural network integrated reinforcement learning W Hu, Z Sun, Y Zhang, Y Li Procedia Manufacturing 39, 1242-1249, 2019 | 9 | 2019 |
| : Lowering the Bound of Misclassification Rate for Sparse Linear Discriminant Analysis via Model Debiasing H Xiong, W Cheng, J Bian, W Hu, Z Sun, Z Guo IEEE transactions on neural networks and learning systems 30 (3), 707-717, 2018 | 9 | 2018 |
| De-biasing Covariance-Regularized Discriminant Analysis. H Xiong, W Cheng, Y Fu, W Hu, J Bian, Z Guo IJCAI, 2889-2897, 2018 | 9 | 2018 |
| AWDA: An Adaptive Wishart Discriminant Analysis H Xiong, W Cheng, W Hu, J Bian, Z Guo ICDM 2017 (2017 IEEE International Conference on Data Mining), New Orleans …, 2017 | 9 | 2017 |
Haoyi XiongMicrosoftVerified email at microsoft.com
