32 citations · 155 across the 38 of their papers we have counts for
7 papers · 1 filter
Sequential Gradient Descent and Quasi-Newton's Method for Change-Point Analysis
Xianyang Zhang, Trisha Dawn
One common approach to detecting change-points is minimizing a cost function over possible numbers and locations of change-points. The framework includes several well-established p…
Powerful Spatial Multiple Testing via Borrowing Neighboring Information
Linsui Deng, Kejun He, Xianyang Zhang
Clustered effects are often encountered in multiple hypothesis testing of spatial signals. In this paper, we propose a new method, termed \textit{two-dimensional spatial multiple t…
Distance and Kernel-Based Measures for Global and Local Two-Sample Conditional Distribution Testing
Jian Yan, Zhuoxi Li, Xianyang Zhang
Testing the equality of two conditional distributions is crucial in various modern applications, including transfer learning and causal inference. Despite its importance, this fund…
Likelihood-based Inference for Random Networks with Changepoints
Daniel Cirkovic, Tiandong Wang, Xianyang Zhang
Generative, temporal network models play an important role in analyzing the dependence structure and evolution patterns of complex networks. Due to the complicated nature of real n…
A General Framework for Powerful Confounder Adjustment in Omics Association Studies
Asmita Roy, Jun Chen, Xianyang Zhang
Genomic data are subject to various sources of confounding, such as demographic variables, biological heterogeneity, and batch effects. To identify genomic features associated with…
A Modern Theory for High-dimensional Cox Regression Models
Hanxuan Ye, Xianyang Zhang, Huijuan Zhou
The proportional hazards model has been extensively used in many fields such as biomedicine to estimate and perform statistical significance testing on the effects of covariates in…
Kernel Two-Sample Tests in High Dimension: Interplay Between Moment Discrepancy and Dimension-and-Sample Orders
Jian Yan, Xianyang Zhang
Motivated by the increasing use of kernel-based metrics for high-dimensional and large-scale data, we study the asymptotic behavior of kernel two-sample tests when the dimension an…