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Xiangyu Wang

Unsupervised Change Detection in Satellite Images with Generative Adversarial Network


Sep 08, 2020
Caijun Ren, Xiangyu Wang, Jian Gao, Huanhuan Chen

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A Direct Approach for Sparse Quadratic Discriminant Analysis


Sep 05, 2018
Binyan Jiang, Xiangyu Wang, Chenlei Leng

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* Updated to the JMLR format 
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Towards Unifying Hamiltonian Monte Carlo and Slice Sampling


Jan 10, 2018
Yizhe Zhang, Xiangyu Wang, Changyou Chen, Ricardo Henao, Kai Fan, Lawrence Carin

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* Advances in Neural Information Processing Systems, pages 1741--1749, year 2016 
 * updated version 
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Proximal Alternating Direction Network: A Globally Converged Deep Unrolling Framework


Dec 15, 2017
Risheng Liu, Xin Fan, Shichao Cheng, Xiangyu Wang, Zhongxuan Luo

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Boosting Variational Inference


Mar 01, 2017
Fangjian Guo, Xiangyu Wang, Kai Fan, Tamara Broderick, David B. Dunson

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* 17 pages, 7 figures 
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No penalty no tears: Least squares in high-dimensional linear models


Jun 16, 2016
Xiangyu Wang, David Dunson, Chenlei Leng

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* Added results for non-sparse models; Added results for elliptical distribution; Added simulations for adaptive lasso 
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Unsupervised Cross-Media Hashing with Structure Preservation


Mar 18, 2016
Xiangyu Wang, Alex Yong-Sang Chia

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DECOrrelated feature space partitioning for distributed sparse regression


Feb 12, 2016
Xiangyu Wang, David Dunson, Chenlei Leng

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* Correct legend errors in Figure 3 
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Parallelizing MCMC with Random Partition Trees


Oct 26, 2015
Xiangyu Wang, Fangjian Guo, Katherine A. Heller, David B. Dunson

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* 25 pages, 9 figures 
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On the consistency theory of high dimensional variable screening


Jun 06, 2015
Xiangyu Wang, Chenlei Leng, David B. Dunson

* adding comments on REC 
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High-dimensional Ordinary Least-squares Projection for Screening Variables


Jun 05, 2015
Xiangyu Wang, Chenlei Leng

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* To appear in JRSS-B 
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Median Selection Subset Aggregation for Parallel Inference


Oct 24, 2014
Xiangyu Wang, Peichao Peng, David Dunson

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Parallelizing MCMC via Weierstrass Sampler


May 25, 2014
Xiangyu Wang, David B. Dunson

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* The original Algorithm 1 removed. Provided some theoretical justification for refinement sampling (Theorem 2). Added a new algorithm in addition to the rejection sampling for handling dimensionality curse. New simulations and graphs (with new colors and designs). A real data analysis is also provided 
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