348 citations · 1.2k across the 81 of their papers we have counts for
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Approximate Factor Models with Strongly Correlated Idiosyncratic Errors
Jiahe Lin, George Michailidis
We consider the estimation of approximate factor models for time series data, where strong serial and cross-sectional correlations amongst the idiosyncratic component are present.…
Regularized Estimation of High-dimensional Factor-Augmented Vector Autoregressive (FAVAR) Models
Jiahe Lin, George Michailidis
A factor-augmented vector autoregressive (FAVAR) model is defined by a VAR equation that captures lead-lag correlations amongst a set of observed variables and latent factors $…
Regularized and Smooth Double Core Tensor Factorization for Heterogeneous Data
Davoud Ataee Tarzanagh, George Michailidis
We introduce a general tensor model suitable for data analytic tasks for {\em heterogeneous} datasets, wherein there are joint low-rank structures within groups of observations, bu…
Spiked Laplacian Graphs: Bayesian Community Detection in Heterogeneous Networks
Leo L Duan, George Michailidis, Mingzhou Ding
In network data analysis, it is becoming common to work with a collection of graphs that exhibit \emph{heterogeneity}. For example, neuroimaging data from patient cohorts are incre…
Analyses of Multi-collection Corpora via Compound Topic Modeling
Clint P. George, Wei Xia, George Michailidis
As electronically stored data grow in daily life, obtaining novel and relevant information becomes challenging in text mining. Thus people have sought statistical methods based on…
Online Distributed Estimation of Principal Eigenspaces
Davoud Ataee Tarzanagh, Mohamad Kazem Shirani Faradonbeh, George Michailidis
Principal components analysis (PCA) is a widely used dimension reduction technique with an extensive range of applications. In this paper, an online distributed algorithm is propos…