8 citations · 15 across the 4 of their papers we have counts for
4 papers · 1 filter
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…
High-dimensional Change-point Detection Using Generalized Homogeneity Metrics
Shubhadeep Chakraborty, Runmin Wang, Xianyang Zhang
Change-point detection is a classical problem in statistics. We address the problem of detecting abrupt changes in the data-generating distributions of a sequence of high-dimension…
A New Framework for Distance and Kernel-based Metrics in High Dimensions
Shubhadeep Chakraborty, Xianyang Zhang
The paper presents new metrics to quantify and test for (i) the equality of distributions and (ii) the independence between two high-dimensional random vectors. We show that the en…
Distance Metrics for Measuring Joint Dependence with Application to Causal Inference
Shubhadeep Chakraborty, Xianyang Zhang
Many statistical applications require the quantification of joint dependence among more than two random vectors. In this work, we generalize the notion of distance covariance to qu…