| Stochastic alternating direction method of multipliers H Ouyang, N He, L Tran, A Gray International Conference on Machine Learning, 80-88, 2013 | 269 | 2013 |
| Scalable kernel methods via doubly stochastic gradients B Dai, B Xie, N He, Y Liang, A Raj, MF Balcan, L Song arXiv preprint arXiv:1407.5599, 2014 | 210 | 2014 |
| SBEED: Convergent reinforcement learning with nonlinear function approximation B Dai, A Shaw, L Li, L Xiao, N He, Z Liu, J Chen, L Song International Conference on Machine Learning (ICML), PMLR 80:1125-1134, 2018 | 138 | 2018 |
| Time-sensitive recommendation from recurrent user activities N Du, Y Wang, N He, J Sun, L Song Advances in Neural Information Processing Systems 28, 3492-3500, 2015 | 124 | 2015 |
| Learning from conditional distributions via dual embeddings B Dai, N He, Y Pan, B Boots, L Song Artificial Intelligence and Statistics, 1458-1467, 2017 | 80 | 2017 |
| Stochastic Generative Hashing B Dai, R Guo, S Kumar, N He, L Song International Conference on Machine Learning, PMLR 70:913-922, 2017 | 64 | 2017 |
| Provable bayesian inference via particle mirror descent B Dai, N He, H Dai, L Song Artificial Intelligence and Statistics, 985-994, 2016 | 58* | 2016 |
| Mirror prox algorithm for multi-term composite minimization and semi-separable problems N He, A Juditsky, A Nemirovski Computational Optimization and Applications 61 (2), 275-319, 2015 | 44* | 2015 |
| Global convergence and variance-reduced optimization for a class of nonconvex-nonconcave minimax problems J Yang, N Kiyavash, N He Advances in Neural Information Processing Systems 33, 2020 | 36 | 2020 |
| Online learning for multivariate hawkes processes Y Yang, J Etesami, N He, N Kiyavash Proceedings of the 31st International Conference on Neural Information …, 2017 | 35 | 2017 |
| On the Convergence Rate of Stochastic Mirror Descent for Nonsmooth Nonconvex Optimization S Zhang, N He arXiv preprint arXiv:1806.04781, 2018 | 31 | 2018 |
| Boosting the Actor with Dual Critic B Dai, A Shaw, N He, L Li, L Song International Conference on Learning Representations, 2017 | 28 | 2017 |
| Learning from conditional distributions via dual kernel embeddings B Dai, N He, Y Pan, B Boots, L Song arXiv preprint arXiv:1607.04579, 2016 | 22 | 2016 |
| Optimization for reinforcement learning: From a single agent to cooperative agents D Lee, N He, P Kamalaruban, V Cevher IEEE Signal Processing Magazine 37 (3), 123-135, 2020 | 21 | 2020 |
| Exponential Family Estimation via Adversarial Dynamics Embedding B Dai, Z Liu, H Dai, N He, A Gretton, L Song, D Schuurmans Advances in Neural Information Processing Systems (NeurIPS), 10977--10988, 2019 | 20 | 2019 |
| Kernel exponential family estimation via doubly dual embedding B Dai, H Dai, A Gretton, L Song, D Schuurmans, N He Proceedings of Machine Learning Research, PMLR 89:2321-2330, 2019 | 19 | 2019 |
| Coupled variational bayes via optimization embedding B Dai, H Dai, N He, W Liu, Z Liu, J Chen, L Xiao, L Song Advances in Neural Information Processing Systems (NeurIPS), 9690-9700, 2018 | 19 | 2018 |
| Point process estimation with mirror prox algorithms N He, Z Harchaoui, Y Wang, L Song Applied Mathematics & Optimization 82 (3), 919-947, 2020 | 16* | 2020 |
| Target-Based Temporal Difference Learning D Lee, N He International Conference on Machine Learning (ICML), PMLR 97:3713-3722, 2019 | 15 | 2019 |
| Biased Stochastic First-Order Methods for Conditional Stochastic Optimization and Applications in Meta Learning Y Hu, S Zhang, X Chen, N He Advances in Neural Information Processing Systems 33, 2020 | 14* | 2020 |
Le SongGeorgia Institute of TechnologyVerified email at cc.gatech.edu
