Karl Rohe
Karl Rohe
Associate Professor of Statistics, UW Madison
Verified email at stat.wisc.edu - Homepage
Title
Cited by
Cited by
Year
Spectral clustering and the high-dimensional stochastic blockmodel
K Rohe, S Chatterjee, B Yu
The Annals of Statistics 39 (4), 1878-1915, 2011
6102011
Regularized spectral clustering under the degree-corrected stochastic blockmodel
T Qin, K Rohe
Advances in Neural Information Processing Systems, 3120-3128, 2013
1802013
Fantope projection and selection: A near-optimal convex relaxation of sparse PCA
VQ Vu, J Cho, J Lei, K Rohe
Advances in neural information processing systems, 2670-2678, 2013
1132013
Fast and accurate detection of evolutionary shifts in Ornstein–Uhlenbeck models
M Khabbazian, R Kriebel, K Rohe, C AnÚ
Methods in Ecology and Evolution 7 (7), 811-824, 2016
992016
Covariate-assisted spectral clustering
N Binkiewicz, JT Vogelstein, K Rohe
Biometrika 104 (2), 361-377, 2017
672017
Co-clustering directed graphs to discover asymmetries and directional communities
K Rohe, T Qin, B Yu
Proceedings of the National Academy of Sciences 113 (45), 12679-12684, 2016
67*2016
Estimating network degree distributions under sampling: An inverse problem, with applications to monitoring social media networks
Y Zhang, ED Kolaczyk, BD Spencer
The Annals of Applied Statistics 9 (1), 166-199, 2015
432015
Preconditioning the Lasso for sign consistency
J Jia, K Rohe
Electronic Journal of Statistics 9 (1), 1150-1172, 2015
40*2015
Attention and amplification in the hybrid media system: The composition and activity of Donald Trump’s Twitter following during the 2016 presidential election
Y Zhang, C Wells, S Wang, K Rohe
New Media & Society 20 (9), 3161-3182, 2018
322018
The lasso under poisson-like heteroscedasticity
J Jia, K Rohe, B Yu
Statistica Sinica, 0
32*
Understanding regularized spectral clustering via graph conductance
Y Zhang, K Rohe
Advances in Neural Information Processing Systems, 10631-10640, 2018
172018
The highest dimensional stochastic blockmodel with a regularized estimator
K Rohe, T Qin, H Fan
Statistica Sinica, 1771-1786, 2014
152014
A critical threshold for design effects in network sampling
K Rohe
The Annals of Statistics 47 (1), 556-582, 2019
14*2019
Novel sampling design for respondent-driven sampling
M Khabbazian, B Hanlon, Z Russek, K Rohe
Electronic Journal of Statistics 11 (2), 4769-4812, 2017
112017
Central limit theorems for network driven sampling
X Li, K Rohe
Electronic Journal of Statistics 11 (2), 4871-4895, 2017
112017
Discovering political topics in Facebook discussion threads with graph contextualization
Y Zhang, M Poux-Berthe, C Wells, K Koc-Michalska, K Rohe
The Annals of Applied Statistics 12 (2), 1096-1123, 2018
9*2018
The blessing of transitivity in sparse and stochastic networks
K Rohe, T Qin
arXiv preprint arXiv:1307.2302, 2013
52013
Asymptotic theory for estimating the singular vectors and values of a partially-observed low rank matrix with noise
J Cho, D Kim, K Rohe
Statistica Sinica, 1921-1948, 2017
42017
Intelligent Initialization and Adaptive Thresholding for Iterative Matrix Completion: Some Statistical and Algorithmic Theory for Adaptive-Impute
J Cho, D Kim, K Rohe
Journal of Computational and Graphical Statistics 28 (2), 323-333, 2019
32019
Generalized least squares can overcome the critical threshold in respondent-driven sampling
S Roch, K Rohe
Proceedings of the National Academy of Sciences 115 (41), 10299-10304, 2018
32018
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Articles 1–20