55 citations · 78 across the 21 of their papers we have counts for
22 papers
A Decorrelating and Debiasing Approach to Simultaneous Inference for High-Dimensional Confounded Models
Yinrui Sun, Li Ma, Yin Xia
Motivated by the simultaneous association analysis with the presence of latent confounders, this paper studies the large-scale hypothesis testing problem for the high-dimensional c…
A tree perspective on stick-breaking models in covariate-dependent mixtures
Akira Horiguchi, Cliburn Chan, Li Ma
Stick-breaking (SB) processes are often adopted in Bayesian mixture models for generating mixing weights. When covariates influence the sizes of clusters, SB mixtures are particula…
NAPA: Neighborhood-Assisted and Posterior-Adjusted Two-sample Inference
Li Ma, Yin Xia, Lexin Li
Two-sample multiple testing problems of sparse spatial data are frequently arising in a variety of scientific applications. In this article, we develop a novel neighborhood-assiste…
Microbiome subcommunity learning with logistic-tree normal latent Dirichlet allocation
Patrick LeBlanc, Li Ma
Mixed-membership (MM) models such as Latent Dirichlet Allocation (LDA) have been applied to microbiome compositional data to identify latent subcommunities of microbial species. Th…
A tree-based model for addressing sparsity and taxa covariance in microbiome compositional count data
Zhuoqun Wang, Jialiang Mao, Li Ma
Microbiome compositional data are often high-dimensional, sparse, and exhibit pervasive cross-sample heterogeneity. Generative modeling is a popular approach to analyze such data,…
Unsupervised tree boosting for learning probability distributions
Naoki Awaya, Li Ma
We propose an unsupervised tree boosting algorithm for inferring the underlying sampling distribution of an i.i.d. sample based on fitting additive tree ensembles in a fashion anal…