348 citations · 1.2k across the 81 of their papers we have counts for
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Robust Estimation of Sparse, High Dimensional Time Series with Polynomial Tails
Sagnik Halder, George Michailidis
High dimensional Vector Autoregressions (VAR) have received a lot of interest recently due to novel applications in health, engineering, finance and the social sciences. Three issu…
Optimal Sparse Estimation of High Dimensional Heavy-tailed Time Series
Sagnik Halder, George Michailidis
Recently, high dimensional vector auto-regressive models (VAR), have attracted a lot of interest, due to novel applications in the health, engineering and social sciences. The pres…
High Dimensional Logistic Regression Under Network Dependence
Somabha Mukherjee, Ziang Niu, Sagnik Halder +2
Logistic regression is key method for modeling the probability of a binary outcome based on a collection of covariates. However, the classical formulation of logistic regression re…
Online detection of local abrupt changes in high-dimensional Gaussian graphical models
Hossein Keshavarz, George Michailidis
The problem of identifying change points in high-dimensional Gaussian graphical models (GGMs) in an online fashion is of interest, due to new applications in biology, economics and…
Change Point Estimation in Panel Data with Temporal and Cross-sectional Dependence
Monika Bhattacharjee, Moulinath Banerjee, George Michailidis
We study the problem of detecting a common change point in large panel data based on a mean shift model, wherein the errors exhibit both temporal and cross-sectional dependence. A…
Change Point Estimation in a Dynamic Stochastic Block Model
Monika Bhattacharjee, Moulinath Banerjee, George Michailidis
We consider the problem of estimating the location of a single change point in a dynamic stochastic block model. We propose two methods of estimating the change point, together wit…