| Tensor clustering with planted structures: Statistical optimality and computational limits Y Luo, AR Zhang The Annals of Statistics 50 (1), 584-613, 2022 | 50 | 2022 |
| ISLET: Fast and optimal low-rank tensor regression via importance sketching AR Zhang, Y Luo, G Raskutti, M Yuan SIAM journal on mathematics of data science 2 (2), 444-479, 2020 | 49 | 2020 |
| Exact clustering in tensor block model: Statistical optimality and computational limit R Han, Y Luo, M Wang, AR Zhang Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2022 | 42 | 2022 |
| Open problem: Average-case hardness of hypergraphic planted clique detection Y Luo, AR Zhang Conference on Learning Theory, 3852-3856, 2020 | 20 | 2020 |
| Diagnosing university student subject proficiency and predicting degree completion in vector space Y Luo, Z Pardos Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 18 | 2018 |
| Low-rank tensor estimation via riemannian gauss-newton: Statistical optimality and second-order convergence Y Luo, AR Zhang The Journal of Machine Learning Research 24 (1), 18274-18321, 2023 | 17 | 2023 |
| Model confidence bounds for variable selection Y Li, Y Luo, D Ferrari, X Hu, Y Qin Biometrics 75 (2), 392-403, 2019 | 17 | 2019 |
| Recursive importance sketching for rank constrained least squares: Algorithms and high-order convergence Y Luo, W Huang, X Li, A Zhang Operations Research 72 (1), 237-256, 2024 | 15 | 2024 |
| A sharp blockwise tensor perturbation bound for orthogonal iteration Y Luo, G Raskutti, M Yuan, AR Zhang Journal of machine learning research 22 (179), 1-48, 2021 | 14 | 2021 |
| A Schatten-q low-rank matrix perturbation analysis via perturbation projection error bound Y Luo, R Han, AR Zhang Linear Algebra and its Applications 630, 225-240, 2021 | 13* | 2021 |
| Tensor-on-tensor regression: Riemannian optimization, over-parameterization, statistical-computational gap, and their interplay Y Luo, AR Zhang arXiv preprint arXiv:2206.08756, 2022 | 10 | 2022 |
| Nonconvex matrix factorization is geodesically convex: Global landscape analysis for fixed-rank matrix optimization from a riemannian perspective Y Luo, NG Trillos arXiv preprint arXiv:2209.15130, 2022 | 8 | 2022 |
| Nonconvex factorization and manifold formulations are almost equivalent in low-rank matrix optimization Y Luo, X Li, AR Zhang arXiv preprint arXiv:2108.01772, 2021 | 6 | 2021 |
| Iterative approximate cross-validation Y Luo, Z Ren, R Barber International Conference on Machine Learning, 23083-23102, 2023 | 4 | 2023 |
| Statistical and computational limits for tensor-on-tensor association detection I Diakonikolas, DM Kane, Y Luo, A Zhang The Thirty Sixth Annual Conference on Learning Theory, 5260-5310, 2023 | 3 | 2023 |
| On geometric connections of embedded and quotient geometries in Riemannian fixed-rank matrix optimization Y Luo, X Li, AR Zhang Mathematics of Operations Research, 2023 | 3 | 2023 |
| Computational Lower Bounds for Graphon Estimation via Low-degree Polynomials Y Luo, C Gao arXiv preprint arXiv:2308.15728, 2023 | 2 | 2023 |
| Rejoinder to Discussions on: Model confidence bounds for variable selection Y Li, Y Luo, D Ferrari, X Hu, Y Qin Biometrics 75 (2), 411-413, 2019 | 2 | 2019 |
| Provable Second-Order Riemannian Gauss-Newton Method for Low-Rank Tensor Estimation ‖ Y Luo, Q Ma, C Zhang, AR Zhang ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 1 | 2022 |
| The Limits of Assumption-free Tests for Algorithm Performance Y Luo, RF Barber arXiv preprint arXiv:2402.07388, 2024 | | 2024 |
Anru ZhangDuke UniversityVerified email at duke.edu
