KarlRohe

Assistant Professor of Statistics,
courtesy appointment in Electrical Engineering, University of Wisconsin--Madison.

Editorial Service: AE at JRSS-B and JNPS.

NETWORK ANALYSIS

Network-driven sampling, community detection, contextualized network analysis.

STATISTICAL MACHINE LEARNING

particularly multivariate methods and clustering.

J Cho, D Kim, and K Rohe. “Intelligent initialization and adaptive thresholding for iterative matrix completion; some statistical and algorithmic theory for adaptive-impute.” [pdf]

X Li and K Rohe. “Central limit theorems for network driven sampling.” [pdf]

M Khabbazian, B Hanlon, Z Russek, and K Rohe. “Novel sampling design for respondent-driven sampling.” [pdf]

M Khabbazian, R Kriebel, K Rohe, and C Ané. “Fast and accurate detection of evolutionary shifts in ornstein-uhlenbeck models.” Methods in Ecology and Evolution, 7(7):811–824, 2016.

T Le, D Bolt, E Camburn, P Goff, and K Rohe. “Latent factors in student-teacher interaction factor analysis.” Accepted in the Journal of Educational and Behavioral Statistics (an ASA journal).

J Cho, D Kim, and K Rohe. “Asymptotic theory for estimating the singular vectors and values of a partially-observed low rank matrix with noise.” Statistica Sinica (accepted). [pdf]

K Rohe, T Qin, and B Yu. “Co-clustering directed graphs to discover asymmetries and directional communities.” Accepted at PNAS. [tech report] [code]

K Rohe. “Network driven sampling; a critical threshold for design effects.” [pdf]

N Binkiewicz, JT Vogelstein, K Rohe. “Covariate Assisted Spectral Clustering.” [pdf]

K Rohe. “Preconditioning for classical relationships: a note relating ridge re- gression and ols p-values to preconditioned sparse penalized regression.” Stat (ISI journal for rapid publication), 4(1):157–166, 2015. [pdf]

V Vu, J Cho, J Lei, K Rohe. “Fantope Projection and Selection: A near-optimal convex relaxation of Sparse PCA”. NIPS 2013. [pdf]

T Qin and K Rohe. “Regularized Spectral Clustering Under the Degree-Corrected Stochastic Blockmodel.” NIPS 2013. [pdf]

K Rohe and T Qin. “The Blessing of Transitivity in Sparse and Stochastic Networks.” [pdf]

J Jia and K Rohe. “Preconditioning to comply with the Irrepresentable Condition.” Electronic Journal of Statistics 2015. [pdf]

K Rohe, T Qin, H Fan. “The Highest Dimensional Stochastic Blockmodel with a Regularized Estimator.” Statistica Sinica. [pdf]

K Rohe, S Chatterjee, and B Yu. “Spectral clustering and the high-dimensional Stochastic Blockmodel.” Annals of Statistics, 39(4):1878–1915, 2011. [pdf]

J Jia, K Rohe, and B Yu. “The Lasso under heteroskedasticity.” Statistica Sinica. [pdf]

December 9, 2016. Wilks Seminar at Princeton ORFE.

July 31, 2016. JSM Chicago.

July 11-22, 2016. Workshop: Theoretical Foundations for Statistical Network Analysis at the Isaac Newton Institute.

April 2, 2016. Population Association of America Session 1131; Innovations in Sampling.

April 1, 2016. Johns Hopkins University; email me for more details.

March 3, 2016. Math and Stat Department Seminar at Boston University.

December 14-18, 2015. Workshop at the Santa Fe Institute.

November 16, 2015. Yale University stat dept.

October 20, 2015. University of Michigan Center for the Study of Complex Systems.

October 8, 2015. The University of Iowa stat dept.

Talks

(let me know if you will be nearby and would like to meet.)

photo courtesy of Frances Tong

This research is supported by NSF grants DMS-1309998, DMS-1612456, and ARO grant W911NF-15-1-0423.