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
583 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