57 citations · 138 across the 14 of their papers we have counts for
14 papers
Sparse estimation of parameter support sets for generalized vector autoregressions by resampling and model aggregation
Trevor D. Ruiz, Sharmodeep Bhattacharyya, Sarah C. Emerson
The central problem we address in this work is estimation of the parameter support set S, the set of indices corresponding to nonzero parameters, in the context of a sparse paramet…
Concentration inequalities for correlated network-valued processes with applications to community estimation and changepoint analysis
Sayak Chatterjee, Shirshendu Chatterjee, Soumendu Sundar Mukherjee +2
Network-valued time series are currently a common form of network data. However, the study of the aggregate behavior of network sequences generated from network-valued stochastic p…
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…
Sparse and Low-bias Estimation of High Dimensional Vector Autoregressive Models
Trevor D. Ruiz, Sharmodeep Bhattacharyya, Mahesh Balasubramanian +1
Vector autoregressive (VAR) models are widely used for causal discovery and forecasting in multivariate time series analysis. In the high-dimensional setting, which is increasingly…
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 (…
Spectral Clustering for Multiple Sparse Networks: I
Sharmodeep Bhattacharyya, Shirshendu Chatterjee
Although much of the focus of statistical works on networks has been on static networks, multiple networks are currently becoming more common among network data sets. Usually, a nu…
Union of Intersections (UoI) for Interpretable Data Driven Discovery and Prediction
Kristofer E. Bouchard, Alejandro F. Bujan, Farbod Roosta-Khorasani +7
The increasing size and complexity of scientific data could dramatically enhance discovery and prediction for basic scientific applications. Realizing this potential, however, requ…
Spectral Clustering and Block Models: A Review And A New Algorithm
Sharmodeep Bhattacharyya, Peter J. Bickel
We focus on spectral clustering of unlabeled graphs and review some results on clustering methods which achieve weak or strong consistent identification in data generated by such m…
Community Detection in Networks using Graph Distance
Sharmodeep Bhattacharyya, Peter J. Bickel
The study of networks has received increased attention recently not only from the social sciences and statistics but also from physicists, computer scientists and mathematicians. O…
Subsampling bootstrap of count features of networks
Sharmodeep Bhattacharyya, Peter J. Bickel
Analysis of stochastic models of networks is quite important in light of the huge influx of network data in social, information and bio sciences, but a proper statistical analysis…