12 citations · 16 across the 4 of their papers we have counts for
8 papers
Numerical Characterization of Support Recovery in Sparse Regression with Correlated Design
Ankit Kumar, Sharmodeep Bhattacharyya, Kristofer Bouchard
Sparse regression is frequently employed in diverse scientific settings as a feature selection method. A pervasive aspect of scientific data that hampers both feature selection and…
Estimating the treatment effect of the juvenile stay-at-home order on SARS-CoV-2 infection spread in Saline County, Arkansas
Neil Hwang, Shirshendu Chatterjee, Yanming Di +1
We investigate the treatment effect of the juvenile stay-at-home order (JSAHO) adopted in Saline County, Arkansas, from April 6 to May 7, in mitigating the growth of SARS-CoV-2 inf…
Consistent detection and optimal localization of all detectable change points in piecewise stationary arbitrarily sparse network-sequences
Sharmodeep Bhattacharyya, Shirshendu Chatterjee, Soumendu Sundar Mukherjee
We consider the offline change point detection and localization problem in the context of piecewise stationary networks, where the observable is a finite sequence of networks. We d…
General Community Detection with Optimal Recovery Conditions for Multi-relational Sparse Networks with Dependent Layers
Sharmodeep Bhattacharyya, Shirshendu Chatterjee
Multilayer and multiplex networks are becoming common network data sets in recent times. We consider the problem of identifying the common community structure for a special type of…
Hierarchical community detection by recursive partitioning
Tianxi Li, Lihua Lei, Sharmodeep Bhattacharyya +4
The problem of community detection in networks is usually formulated as finding a single partition of the network into some "correct" number of communities. We argue that it is mor…
Optimizing the Union of Intersections LASSO () and Vector Autoregressive () Algorithms for Improved Statistical Estimation at Scale
Mahesh Balasubramanian, Trevor Ruiz, Brandon Cook +4
The analysis of scientific data of increasing size and complexity requires statistical machine learning methods that are both interpretable and predictive. Union of Intersections (…