| Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates D Yin, Y Chen, K Ramchandran, P Bartlett International Conference on Machine Learning, 2018, 2018 | 1563 | 2018 |
| User association for load balancing in heterogeneous cellular networks Q Ye, B Rong, Y Chen, M Al-Shalash, C Caramanis, JG Andrews IEEE Transactions on Wireless Communications 12 (6), 2706-2716, 2013 | 1450 | 2013 |
| Tensor robust principal component analysis with a new tensor nuclear norm C Lu, J Feng, Y Chen, W Liu, Z Lin, S Yan IEEE transactions on pattern analysis and machine intelligence 42 (4), 925-938, 2019 | 837 | 2019 |
| Distributed Statistical Machine Learning in Adversarial Settings: Byzantine Gradient Descent Y Chen, L Su, J Xu Proceedings of the ACM on Measurement and Analysis of Computing Systems 1 (2 …, 2017 | 692 | 2017 |
| Tensor Robust Principal Component Analysis: Exact Recovery of Corrupted Low-Rank Tensors via Convex Optimization C Lu, J Feng, Y Chen, W Liu, Z Lin, S Yan IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 5249-5257, 2016 | 572 | 2016 |
| Fast low-rank estimation by projected gradient descent: General statistical and algorithmic guarantees Y Chen, MJ Wainwright arXiv preprint arXiv:1509.03025, 2015 | 335 | 2015 |
| Fast Algorithms for Robust PCA via Gradient Descent X Yi, D Park, Y Chen, C Caramanis Advances in neural information processing systems, 2016 | 308 | 2016 |
| Statistical-computational tradeoffs in planted problems and submatrix localization with a growing number of clusters and submatrices Y Chen, J Xu Journal of Machine Learning Research 17 (27), 1-57, 2016 | 240 | 2016 |
| Completing any low-rank matrix, provably Y Chen, S Bhojanapalli, S Sanghavi, R Ward Journal of Machine Learning Research 16, 2999-3034, 2015 | 234* | 2015 |
| Incoherence-optimal matrix completion Y Chen IEEE Transactions on Information Theory 61 (5), 2909-2923, 2015 | 231 | 2015 |
| Low-rank matrix recovery from errors and erasures Y Chen, A Jalali, S Sanghavi, C Caramanis IEEE Transactions on Information Theory 59 (7), 4324-4337, 2013 | 223 | 2013 |
| Random Features for Kernel Approximation: A Survey in Algorithms, Theory, and Beyond F Liu, X Huang, Y Chen, JAK Suykens IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020 | 197 | 2020 |
| Clustering sparse graphs Y Chen, S Sanghavi, H Xu Advances in neural information processing systems, 2204-2212, 2012 | 196 | 2012 |
| Harnessing Structures in Big Data via Guaranteed Low-Rank Matrix Estimation Y Chen, Y Chi IEEE Signal Processing Magazine 35 (4), 14-31, 2018 | 183 | 2018 |
| Robust Sparse Regression under Adversarial Corruption. Y Chen, C Caramanis, S Mannor International Conference on Machine Learning, 774-782, 2013 | 171 | 2013 |
| Learning zero-sum simultaneous-move markov games using function approximation and correlated equilibrium Q Xie, Y Chen, Z Wang, Z Yang Conference on learning theory, 3674-3682, 2020 | 153 | 2020 |
| Robust matrix completion with corrupted columns Y Chen, H Xu, C Caramanis, S Sanghavi Proceedings of the 28 th International Conference on Machine Learning, 2011 | 147 | 2011 |
| Clustering partially observed graphs via convex optimization. Y Chen, A Jalali, S Sanghavi, H Xu Journal of Machine Learning Research 15 (1), 2213-2238, 2014 | 146 | 2014 |
| Convexified Modularity Maximization for Degree-corrected Stochastic Block Models Y Chen, X Li, J Xu The Annals of Statistics 46 (4), 1573-1602, 2015 | 129 | 2015 |
| Defending Against Saddle Point Attack in Byzantine-Robust Distributed Learning D Yin, Y Chen, K Ramchandran, P Bartlett International Conference on Machine Learning, 2019 | 123 | 2019 |
Constantine CaramanisProfessor of Electrical and Computer Engineering, UT Austin在 utexas.edu 的电子邮件经过验证
