49 citations · 58 across the 8 of their papers we have counts for
4 papers · 1 filter
Computational Inference for Directions in Canonical Correlation Analysis
Daniel Kessler, Elizaveta Levina
Canonical Correlation Analysis (CCA) is a method for analyzing pairs of random vectors; it learns a sequence of paired linear transformations such that the resultant canonical vari…
Predicting Responses from Weighted Networks with Node Covariates in an Application to Neuroimaging
Daniel Kessler, Keith Levin, Elizaveta Levina
We consider the setting where many networks are observed on a common node set, and each observation comprises edge weights of a network, covariates observed at each node, and an ov…
Approximate Post-Selective Inference for Regression with the Group LASSO
Snigdha Panigrahi, Peter W. MacDonald, Daniel Kessler
After selection with the Group LASSO (or generalized variants such as the overlapping, sparse, or standardized Group LASSO), inference for the selected parameters is unreliable in…
Network classification with applications to brain connectomics
Jesús D. Arroyo-Relión, Daniel Kessler, Elizaveta Levina +1
While statistical analysis of a single network has received a lot of attention in recent years, with a focus on social networks, analysis of a sample of networks presents its own c…