100 citations · 275 across the 10 of their papers we have counts for
10 papers
Boosting Variational Inference
Fangjian Guo, Xiangyu Wang, Kai Fan +2
Variational inference (VI) provides fast approximations of a Bayesian posterior in part because it formulates posterior approximation as an optimization problem: to find the closes…
DECOrrelated feature space partitioning for distributed sparse regression
Xiangyu Wang, David Dunson, Chenlei Leng
Fitting statistical models is computationally challenging when the sample size or the dimension of the dataset is huge. An attractive approach for down-scaling the problem size is…
Towards Unifying Hamiltonian Monte Carlo and Slice Sampling
Yizhe Zhang, Xiangyu Wang, Changyou Chen +3
We unify slice sampling and Hamiltonian Monte Carlo (HMC) sampling, demonstrating their connection via the Hamiltonian-Jacobi equation from Hamiltonian mechanics. This insight enab…
A Direct Approach for Sparse Quadratic Discriminant Analysis
Binyan Jiang, Xiangyu Wang, Chenlei Leng
Quadratic discriminant analysis (QDA) is a standard tool for classification due to its simplicity and flexibility. Because the number of its parameters scales quadratically with th…
High-dimensional Ordinary Least-squares Projection for Screening Variables
Xiangyu Wang, Chenlei Leng
Variable selection is a challenging issue in statistical applications when the number of predictors far exceeds the number of observations . In this ultra-high dimensional s…
Parallelizing MCMC with Random Partition Trees
Xiangyu Wang, Fangjian Guo, Katherine A. Heller +1
The modern scale of data has brought new challenges to Bayesian inference. In particular, conventional MCMC algorithms are computationally very expensive for large data sets. A pro…
No penalty no tears: Least squares in high-dimensional linear models
Xiangyu Wang, David Dunson, Chenlei Leng
Ordinary least squares (OLS) is the default method for fitting linear models, but is not applicable for problems with dimensionality larger than the sample size. For these problems…
On the consistency theory of high dimensional variable screening
Xiangyu Wang, Chenlei Leng, David B. Dunson
Variable screening is a fast dimension reduction technique for assisting high dimensional feature selection. As a preselection method, it selects a moderate size subset of candidat…
Median Selection Subset Aggregation for Parallel Inference
Xiangyu Wang, Peichao Peng, David Dunson
For massive data sets, efficient computation commonly relies on distributed algorithms that store and process subsets of the data on different machines, minimizing communication co…
Parallelizing MCMC via Weierstrass Sampler
Xiangyu Wang, David B. Dunson
With the rapidly growing scales of statistical problems, subset based communication-free parallel MCMC methods are a promising future for large scale Bayesian analysis. In this art…