284 citations · 587 across the 49 of their papers we have counts for
11 papers · 1 filter
Joint Estimation and Inference for Multi-Experiment Networks of High-Dimensional Point Processes
Xu Wang, Ali Shojaie
Modern high-dimensional point process data, especially those from neuroscience experiments, often involve observations from multiple conditions and/or experiments. Networks of inte…
Causal Discovery in High-Dimensional Point Process Networks with Hidden Nodes
Xu Wang, Ali Shojaie
Thanks to technological advances leading to near-continuous time observations, emerging multivariate point process data offer new opportunities for causal discovery. However, a key…
Direct estimation and inference of differential Granger causality between two high-dimensional time series
Yue Wang, Jing Ma, Ali Shojaie
Comparing dependence structures between two related multivariate time series is of fundamental interest in many scientific applications, where changes may occur in both directed te…
Interaction Models and Generalized Score Matching for Compositional Data
Shiqing Yu, Mathias Drton, Ali Shojaie
Applications such as the analysis of microbiome data have led to renewed interest in statistical methods for compositional data, i.e., multivariate data in the form of probability…
Causal Structural Learning Via Local Graphs
Wenyu Chen, Mathias Drton, Ali Shojaie
We consider the problem of learning causal structures in sparse high-dimensional settings that may be subject to the presence of (potentially many) unmeasured confounders, as well…
Nonparametric causal structure learning in high dimensions
Shubhadeep Chakraborty, Ali Shojaie
The PC and FCI algorithms are popular constraint-based methods for learning the structure of directed acyclic graphs (DAGs) in the absence and presence of latent and selection vari…
Definite Non-Ancestral Relations and Structure Learning
Wenyu Chen, Mathias Drton, Ali Shojaie
In causal graphical models based on directed acyclic graphs (DAGs), directed paths represent causal pathways between the corresponding variables. The variable at the beginning of s…
Inference on function-valued parameters using a restricted score test
Aaron Hudson, Marco Carone, Ali Shojaie
It is often of interest to make inference on an unknown function that is a local parameter of the data-generating mechanism, such as a density or regression function. Such estimand…
Granger Causality: A Review and Recent Advances
Ali Shojaie, Emily B. Fox
Introduced more than a half century ago, Granger causality has become a popular tool for analyzing time series data in many application domains, from economics and finance to genom…
On the Optimality of Nuclear-norm-based Matrix Completion for Problems with Smooth Non-linear Structure
Yunhua Xiang, Tianyu Zhang, Xu Wang +2
Originally developed for imputing missing entries in low rank, or approximately low rank matrices, matrix completion has proven widely effective in many problems where there is no…
Generalized Matrix Decomposition Regression: Estimation and Inference for Two-way Structured Data
Yue Wang, Ali Shojaie, Timothy W. Randolph +2
This paper studies high-dimensional regression with two-way structured data. To estimate the high-dimensional coefficient vector, we propose the generalized matrix decomposition re…