| High-dimensional regression with noisy and missing data: Provable guarantees with non-convexity PL Loh, MJ Wainwright Advances in neural information processing systems 24, 2011 | 670 | 2011 |
| Regularized M-estimators with nonconvexity: Statistical and algorithmic theory for local optima PL Loh, MJ Wainwright Advances in Neural Information Processing Systems 26, 2013 | 600 | 2013 |
| Statistical consistency and asymptotic normality for high-dimensional robust -estimators PL Loh | 236 | 2017 |
| Structure estimation for discrete graphical models: Generalized covariance matrices and their inverses PL Loh, MJ Wainwright Advances in Neural Information Processing Systems 25, 2012 | 217 | 2012 |
| Support recovery without incoherence: A case for nonconvex regularization PL Loh, MJ Wainwright | 191 | 2017 |
| High-dimensional learning of linear causal networks via inverse covariance estimation PL Loh, P Bühlmann The Journal of Machine Learning Research 15 (1), 3065-3105, 2014 | 189 | 2014 |
| Machine learning to detect signatures of disease in liquid biopsies–a user's guide J Ko, SN Baldassano, PL Loh, K Kording, B Litt, D Issadore Lab on a Chip 18 (3), 395-405, 2018 | 128 | 2018 |
| Adversarial risk bounds via function transformation J Khim, PL Loh arXiv preprint arXiv:1810.09519, 2018 | 115 | 2018 |
| Generalization error bounds for noisy, iterative algorithms A Pensia, V Jog, PL Loh 2018 IEEE International Symposium on Information Theory (ISIT), 546-550, 2018 | 115 | 2018 |
| Optimal rates for community estimation in the weighted stochastic block model M Xu, V Jog, PL Loh The Annals of Statistics 48 (1), 183-204, 2020 | 79 | 2020 |
| Information-theoretic bounds for exact recovery in weighted stochastic block models using the Renyi divergence V Jog, PL Loh arXiv preprint arXiv:1509.06418, 2015 | 73 | 2015 |
| High-dimensional robust precision matrix estimation: Cellwise corruption under -contamination PL Loh, XL Tan | 59 | 2018 |
| Confidence sets for the source of a diffusion in regular trees J Khim, PL Loh IEEE Transactions on Network Science and Engineering 4 (1), 27-40, 2016 | 58 | 2016 |
| Robust regression with covariate filtering: Heavy tails and adversarial contamination A Pensia, V Jog, PL Loh Journal of the American Statistical Association, 1-40, 2024 | 53 | 2024 |
| Does data augmentation lead to positive margin? S Rajput, Z Feng, Z Charles, PL Loh, D Papailiopoulos International Conference on Machine Learning, 5321-5330, 2019 | 43 | 2019 |
| Analysis of centrality in sublinear preferential attachment trees via the Crump-Mode-Jagers branching process V Jog, PL Loh IEEE Transactions on Network Science and Engineering 4 (1), 1-12, 2016 | 37 | 2016 |
| RNN-Based online anomaly detection in nuclear reactors for highly imbalanced datasets with uncertainty M Kim, E Ou, PL Loh, T Allen, R Agasie, K Liu Nuclear Engineering and Design 364, 110699, 2020 | 35 | 2020 |
| Corrupted and missing predictors: Minimax bounds for high-dimensional linear regression PL Loh, MJ Wainwright 2012 IEEE International Symposium on Information Theory Proceedings, 2601-2605, 2012 | 33 | 2012 |
| Persistence of centrality in random growing trees V Jog, PL Loh Random Structures & Algorithms 52 (1), 136-157, 2018 | 29 | 2018 |
| Differentially private inference via noisy optimization M Avella-Medina, C Bradshaw, PL Loh The Annals of Statistics 51 (5), 2067-2092, 2023 | 28 | 2023 |
