| A convergence theory for deep learning via over-parameterization Z Allen-Zhu, Y Li, Z Song 36th International Conference on Machine Learning (ICML), 242-252, 2019 | 1172 | 2019 |
| Towards fast computation of certified robustness for relu networks TW Weng, H Zhang, H Chen, Z Song, CJ Hsieh, D Boning, IS Dhillon, ... 35th International Conference on Machine Learning (ICML), 5273-5282, 2018 | 634 | 2018 |
| Recovery guarantees for one-hidden-layer neural networks K Zhong, Z Song, P Jain, PL Bartlett, IS Dhillon 34th International Conference on Machine Learning (ICML), 4140-4149, 2017 | 323 | 2017 |
| Solving linear programs in the current matrix multiplication time MB Cohen, YT Lee, Z Song Journal of the ACM (JACM) 68, 1--39, 2021 | 268 | 2021 |
| Solving linear programs in the current matrix multiplication time MB Cohen, YT Lee, Z Song 51th Annual ACM Symposium on Theory of Computing (STOC), 938-942, 2019 | 268 | 2019 |
| On the convergence rate of training recurrent neural networks Z Allen-Zhu, Y Li, Z Song Neural Information Processing Systems (NeurIPS), 6673-6685, 2019 | 158 | 2019 |
| The limitations of adversarial training and the blind-spot attack H Zhang, H Chen, Z Song, D Boning, IS Dhillon, CJ Hsieh The 7th International Conference on Learning Representations (ICLR), 2019 | 126 | 2019 |
| Low rank approximation with entrywise -norm error Z Song, DP Woodruff, P Zhong 49th Annual ACM Symposium on Theory of Computing (STOC), 688-701, 2017 | 119 | 2017 |
| Parallel graph connectivity in log diameter rounds A Andoni, Z Song, C Stein, Z Wang, P Zhong 59th Annual IEEE Symposium on Foundations of Computer Science (FOCS), 674-685, 2018 | 97 | 2018 |
| Relative error tensor low rank approximation Z Song, DP Woodruff, P Zhong 30th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), 2772-2789, 2019 | 93 | 2019 |
| Minimum Cost Flows, MDPs, and -Regression in Nearly Linear Time for Dense Instances J van den Brand, Y Tat Lee, YP Liu, T Saranurak, A Sidford, Z Song, ... 53rd Annual ACM Symposium on Theory of Computing (STOC), 2021 | 92 | 2021 |
| Solving Empirical Risk Minimization in the Current Matrix Multiplication Time YT Lee, Z Song, Q Zhang Conference on Learning Theory (COLT), 2140-2157, 2019 | 90 | 2019 |
| Bipartite Matching in Nearly-linear Time on Moderately Dense Graphs J van den Brand, YT Lee, D Nanongkai, R Peng, T Saranurak, A Sidford, ... 61st Annual IEEE Symposium on Foundations of Computer Science (FOCS), 2020 | 89 | 2020 |
| Faster dynamic matrix inverse for faster lps S Jiang, Z Song, O Weinstein, H Zhang 53rd Annual ACM Symposium on Theory of Computing (STOC), 2021 | 88 | 2021 |
| InstaHide: Instance-hiding Schemes for Private Distributed Learning Y Huang, Z Song, K Li, S Arora 37th International Conference on Machine Learning (ICML), 2020 | 81 | 2020 |
| Weighted low rank approximations with provable guarantees I Razenshteyn, Z Song, DP Woodruff 48th annual ACM symposium on Theory of Computing (STOC), 250-263, 2016 | 81 | 2016 |
| Evaluating gradient inversion attacks and defenses in federated learning Y Huang, S Gupta, Z Song, K Li, S Arora Advances in Neural Information Processing Systems 34, 7232-7241, 2021 | 79 | 2021 |
| Solving tall dense linear programs in nearly linear time J van den Brand, Y Tat Lee, A Sidford, Z Song 52nd Annual ACM Symposium on Theory of Computing (STOC), 775-788, 2020 | 72 | 2020 |
| Quadratic Suffices for Over-parametrization via Matrix Chernoff Bound Z Song, X Yang arXiv preprint arXiv:1906.03593, 2019 | 72 | 2019 |
| An Improved Cutting Plane Method for Convex Optimization, Convex-Concave Games and its Applications H Jiang, YT Lee, Z Song, SC Wong 52nd Annual ACM Symposium on Theory of Computing (STOC), 944-953, 2020 | 70 | 2020 |
David WoodruffProfessor of Computer Science, Carnegie Mellon UniversityVerified email at cs.cmu.edu
