Deep hyperspherical learning W Liu, YM Zhang, X Li, Z Yu, B Dai, T Zhao, L Song Advances in neural information processing systems 30, 2017 | 148 | 2017 |
The flare package for high dimensional linear regression and precision matrix estimation in R X Li, T Zhao, X Yuan, H Liu Journal of Machine Learning Research, 553-557, 2015 | 130* | 2015 |
Symmetry, Saddle Points, and Global Optimization Landscape of Nonconvex Matrix Factorization X Li, J Lu, R Arora, J Haupt, H Liu, Z Wang, T Zhao IEEE Transactions on Information Theory 65 (6), 3489 - 3514, 2019 | 113* | 2019 |
Stochastic variance reduced optimization for nonconvex sparse learning X Li, T Zhao, R Arora, H Liu, J Haupt Proceedings of the 33rd International Conference on Machine Learning, 917-925, 2016 | 107* | 2016 |
Zo-adamm: Zeroth-order adaptive momentum method for black-box optimization X Chen, S Liu, K Xu, X Li, X Lin, M Hong, D Cox Advances in neural information processing systems 32, 2019 | 105 | 2019 |
huge: High-dimensional undirected graph estimation T Zhao, X Li, H Liu, K Roeder, J Lafferty, L Wasserman URL http://CRAN. R-project. org/package= huge. R package version 1 (7), 2015 | 81* | 2015 |
On tighter generalization bound for deep neural networks: Cnns, resnets, and beyond X Li, J Lu, Z Wang, J Haupt, T Zhao arXiv preprint arXiv:1806.05159, 2018 | 71 | 2018 |
Towards black-box iterative machine teaching W Liu, B Dai, X Li, Z Liu, J Rehg, L Song International Conference on Machine Learning, 3141-3149, 2018 | 67 | 2018 |
On Generalization Bounds of a Family of Recurrent Neural Networks M Chen, X Li, T Zhao International Conference on Artificial Intelligence and Statistics (arXiv …, 2020 | 62 | 2020 |
Identifying Outliers in Large Matrices via Randomized Adaptive Compressive Sampling X Li, J Haupt IEEE Trans. Signal Processing, 1792-1807, 2015 | 61 | 2015 |
An Improved Convergence Analysis of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization X Li, T Zhao, R Arora, H Liu, M Hong Proceedings of the 19th International Conference on Artificial Intelligence …, 2016 | 53* | 2016 |
Over-parameterized adversarial training: An analysis overcoming the curse of dimensionality Y Zhang, O Plevrakis, SS Du, X Li, Z Song, S Arora Advances in Neural Information Processing Systems 33, 679-688, 2020 | 52 | 2020 |
On computation and generalization of generative adversarial imitation learning M Chen, Y Wang, T Liu, Z Yang, X Li, Z Wang, T Zhao arXiv preprint arXiv:2001.02792, 2020 | 45 | 2020 |
Near optimal sketching of low-rank tensor regression X Li, J Haupt, D Woodruff Advances in Neural Information Processing Systems 30, 2017 | 38 | 2017 |
Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and Python J Ge, X Li, H Jiang, H Liu, T Zhang, M Wang, T Zhao Journal of Machine Learning Research, 2019 | 33* | 2019 |
Zeroth-order stochastic projected gradient descent for nonconvex optimization S Liu, X Li, PY Chen, J Haupt, L Amini 2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP …, 2018 | 27 | 2018 |
A First Order Free Lunch for SQRT-Lasso X Li, J Haupt, R Arora, H Liu, M Hong, T Zhao arXiv preprint arXiv:1605.07950, 2016 | 22* | 2016 |
On constrained nonconvex stochastic optimization: A case study for generalized eigenvalue decomposition Z Chen, X Li, L Yang, J Haupt, T Zhao The 22nd International Conference on Artificial Intelligence and Statistics …, 2019 | 20* | 2019 |
Noodl: Provable online dictionary learning and sparse coding S Rambhatla, X Li, J Haupt arXiv preprint arXiv:1902.11261, 2019 | 20 | 2019 |
On quadratic convergence of DC proximal Newton algorithm in nonconvex sparse learning X Li, L Yang, J Ge, J Haupt, T Zhang, T Zhao Advances in neural information processing systems 30, 2017 | 16 | 2017 |