118 citations · 351 across the 40 of their papers we have counts for
13 papers · 1 filter
Scalable and non-iterative graphical model estimation
Kshitij Khare, Syed Rahman, Bala Rajaratnam +1
Graphical models have found widespread applications in many areas of modern statistics and machine learning. Iterative Proportional Fitting (IPF) and its variants have become the d…
A generalized likelihood based Bayesian approach for scalable joint regression and covariance selection in high dimensions
Srijata Samanta, Kshitij Khare, George Michailidis
The paper addresses joint sparsity selection in the regression coefficient matrix and the error precision (inverse covariance) matrix for high-dimensional multivariate regression m…
B-CONCORD -- A scalable Bayesian high-dimensional precision matrix estimation procedure
Peyman Jalali, Kshitij Khare, George Michailidis
Sparse estimation of the precision matrix under high-dimensional scaling constitutes a canonical problem in statistics and machine learning. Numerous regression and likelihood base…
A Bayesian Approach to Joint Estimation of Multiple Graphical Models
Peyman Jalali, Kshitij Khare, George Michailidis
The problem of joint estimation of multiple graphical models from high dimensional data has been studied in the statistics and machine learning literature, due to its importance in…
Consistent estimation of the spectrum of trace class data augmentation algorithms
Saptarshi Chakraborty, Kshitij Khare
Markov chain Monte Carlo is widely used in a variety of scientific applications to generate approximate samples from intractable distributions. A thorough understanding of the conv…
Posterior Graph Selection and Estimation Consistency for High-dimensional Bayesian DAG Models
Xuan Cao, Kshitij Khare, Malay Ghosh
Covariance estimation and selection for high-dimensional multivariate datasets is a fundamental problem in modern statistics. Gaussian directed acyclic graph (DAG) models are a pop…