| Adaptive estimation in structured factor models with applications to overlapping clustering X Bing, F Bunea, Y Ning, M Wegkamp | 40 | 2020 |
| Adaptive estimation of the rank of the coefficient matrix in high-dimensional multivariate response regression models X Bing, MH Wegkamp The Annals of Statistics 47 (6), 3157-3184, 2019 | 30 | 2019 |
| A fast algorithm with minimax optimal guarantees for topic models with an unknown number of topics X Bing, F Bunea, M Wegkamp | 24 | 2020 |
| Optimal estimation of sparse topic models X Bing, F Bunea, M Wegkamp Journal of machine learning research 21 (177), 1-45, 2020 | 21 | 2020 |
| Prediction under latent factor regression: Adaptive pcr, interpolating predictors and beyond X Bing, F Bunea, S Strimas-Mackey, M Wegkamp Journal of Machine Learning Research 22 (177), 1-50, 2021 | 12 | 2021 |
| A fast algorithm with minimax optimal guarantees for topic models with an unknown number of topics X Bing, F Bunea, M Wegkamp arXiv preprint arXiv:1805.06837, 2018 | 11 | 2018 |
| Inference in latent factor regression with clusterable features X Bing, F Bunea, M Wegkamp Bernoulli 28 (2), 997-1020, 2022 | 10 | 2022 |
| Adaptive estimation in multivariate response regression with hidden variables X Bing, Y Ning, Y Xu The annals of statistics 50 (2), 640-672, 2022 | 9 | 2022 |
| Essential regression: a generalizable framework for inferring causal latent factors from multi-omic datasets X Bing, T Lovelace, F Bunea, M Wegkamp, SP Kasturi, H Singh, ... Patterns 3 (5), 2022 | 8 | 2022 |
| The sketched Wasserstein distance for mixture distributions X Bing, F Bunea, J Niles-Weed arXiv preprint arXiv:2206.12768, 2022 | 7 | 2022 |
| Essential regression X Bing, F Bunea, M Wegkamp, S Strimas-Mackey arXiv preprint arXiv:1905.12696, 2019 | 7 | 2019 |
| Likelihood estimation of sparse topic distributions in topic models and its applications to Wasserstein document distance calculations X Bing, F Bunea, S Strimas-Mackey, M Wegkamp The Annals of Statistics 50 (6), 3307-3333, 2022 | 6 | 2022 |
| Adaptive estimation of multivariate regression with hidden variables X Bing, Y Ning, Y Xu arXiv preprint arXiv:2003.13844, 2020 | 6 | 2020 |
| Latent model-based clustering for biological discovery X Bing, F Bunea, M Royer, J Das Iscience 14, 125-135, 2019 | 6 | 2019 |
| Inference in high-dimensional multivariate response regression with hidden variables X Bing, W Cheng, H Feng, Y Ning Journal of the American Statistical Association, 1-12, 2023 | 5 | 2023 |
| Prediction in latent factor regression: Adaptive pcr and beyond X Bing, F Bunea, S Strimas-Mackey, M Wegkamp arXiv preprint arXiv:2007.10050, 2020 | 5 | 2020 |
| Sparse latent factor models with pure variables for overlapping clustering X Bing, F Bunea, Y Ning, M Wegkamp arXiv preprint arXiv:1704.06977, 2017 | 5 | 2017 |
| Inference in interpretable latent factor regression models X Bing, F Bunea, M Wegkamp arXiv preprint arXiv:1905.12696, 2019 | 4 | 2019 |
| Detecting approximate replicate components of a high-dimensional random vector with latent structure X Bing, F Bunea, M Wegkamp Bernoulli 29 (2), 1368-1391, 2023 | 3 | 2023 |
| Unique sparse decomposition of low rank matrices D Jin, X Bing, Y Zhang Advances in Neural Information Processing Systems 34, 523-535, 2021 | 3 | 2021 |
Marten WegkampProfessor of Mathematics and Statistical Sciences, Cornell UniversityVerified email at cornell.edu
