| Solving (most) of a set of quadratic equalities: Composite optimization for robust phase retrieval JC Duchi, F Ruan Information and Inference: A Journal of the IMA 8 (3), 471-529, 2019 | 126 | 2019 |
| The generalization error of max-margin linear classifiers: High-dimensional asymptotics in the overparametrized regime A Montanari, F Ruan, Y Sohn, J Yan arXiv preprint arXiv:1911.01544, 2019 | 122 | 2019 |
| Stochastic methods for composite and weakly convex optimization problems JC Duchi, F Ruan SIAM Journal on Optimization 28 (4), 3229-3259, 2018 | 91 | 2018 |
| Sparse recovery via differential inclusions S Osher, F Ruan, J Xiong, Y Yao, W Yin Applied and Computational Harmonic Analysis 41 (2), 436-469, 2016 | 59 | 2016 |
| Lassonet: Neural networks with feature sparsity I Lemhadri, F Ruan, R Tibshirani International Conference on Artificial Intelligence and Statistics, 10-18, 2021 | 45* | 2021 |
| Stochastic methods for composite optimization problems JC Duchi, F Ruan Preprint, 2017 | 36 | 2017 |
| Asymptotic optimality in stochastic optimization JC Duchi, F Ruan The Annals of Statistics 49 (1), 21-48, 2021 | 35* | 2021 |
| The right complexity measure in locally private estimation: It is not the fisher information JC Duchi, F Ruan arXiv preprint arXiv:1806.05756, 2018 | 34 | 2018 |
| Multiclass classification, information, divergence and surrogate risk J Duchi, K Khosravi, F Ruan The Annals of Statistics 46 (6B), 3246-3275, 2018 | 30 | 2018 |
| Minimax bounds on stochastic batched convex optimization J Duchi, F Ruan, C Yun Conference On Learning Theory, 3065-3162, 2018 | 24 | 2018 |
| Bandit Learning in Decentralized Matching Markets. LT Liu, F Ruan, H Mania, MI Jordan J. Mach. Learn. Res. 22, 211:1-211:34, 2021 | 20 | 2021 |
| Is temporal difference learning optimal? an instance-dependent analysis K Khamaru, A Pananjady, F Ruan, MJ Wainwright, MI Jordan arXiv preprint arXiv:2003.07337, 2020 | 20 | 2020 |
| Local asymptotics for some stochastic optimization problems: Optimality, constraint identification, and dual averaging J Duchi, F Ruan arXiv preprint arXiv:1612.05612, 2016 | 11 | 2016 |
| Adapting to unknown noise distribution in matrix denoising A Montanari, F Ruan, J Yan arXiv preprint arXiv:1810.02954, 2018 | 10 | 2018 |
| Is temporal difference learning optimal? an instance-dependent analysis K Khamaru, A Pananjady, F Ruan, MJ Wainwright, MI Jordan SIAM Journal on Mathematics of Data Science 3 (4), 1013-1040, 2021 | 9 | 2021 |
| Characterizing listener engagement with popular songs using large-scale music discovery data B Kaneshiro, F Ruan, CW Baker, J Berger Frontiers in psychology 8, 416, 2017 | 8 | 2017 |
| A constrained risk inequality for general losses J Duchi, F Ruan International Conference on Artificial Intelligence and Statistics, 802-810, 2021 | 5 | 2021 |
| A Self-Penalizing Objective Function for Scalable Interaction Detection K Liu, F Ruan arXiv preprint arXiv:2011.12215, 0 | 2 | |
| Taming Nonconvexity in Kernel Feature Selection---Favorable Properties of the Laplace Kernel F Ruan, K Liu, MI Jordan arXiv preprint arXiv:2106.09387, 2021 | 1 | 2021 |
| A Tutorial on: R Package for the Linearized Bregman Algorithm in High-Dimensional Statistics J Xiong, F Ruan, Y Yao Handbook of Big Data Analytics, 425-453, 2018 | 1 | 2018 |
John DuchiAssociate Professor of Statistics and Electrical Engineering, Stanford Universitystanford.edu의 이메일 확인됨
