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 | 649 | 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 | 582 | 2013 |
Statistical consistency and asymptotic normality for high-dimensional robust -estimators PL Loh | 228 | 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 | 209 | 2012 |
Support recovery without incoherence: A case for nonconvex regularization PL Loh, MJ Wainwright | 185 | 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 | 176 | 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 | 123 | 2018 |
Adversarial risk bounds via function transformation J Khim, PL Loh arXiv preprint arXiv:1810.09519, 2018 | 109 | 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 | 109 | 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 | 71 | 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 | 69 | 2015 |
High-dimensional robust precision matrix estimation: Cellwise corruption under -contamination PL Loh, XL Tan | 57 | 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 | 56 | 2016 |
Robust regression with covariate filtering: Heavy tails and adversarial contamination A Pensia, V Jog, PL Loh arXiv preprint arXiv:2009.12976, 2020 | 50 | 2020 |
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 | 41 | 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 | 35 | 2016 |
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 |
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 | 30 | 2020 |
Persistence of centrality in random growing trees V Jog, PL Loh Random Structures & Algorithms 52 (1), 136-157, 2018 | 27 | 2018 |
Extracting robust and accurate features via a robust information bottleneck A Pensia, V Jog, PL Loh IEEE Journal on Selected Areas in Information Theory 1 (1), 131-144, 2020 | 26 | 2020 |