Yun Yang
I joined the Statistics Department at Florida State University as an Assistant Professor in 2016. Before that, I was a postdoctoral researcher in the EECS department at University of California, Berkeley, working with Martin J. Wainwright and Michael I. Jordan. 

I obtained my Ph.D. in the Department of Statistical Science at Duke University in 2014. My advisors were David B. Dunson and Surya T. Tokdar. I received my B.S. in Mathematics from Tsinghua University in 2011.

My research interests lie broadly in machine learning, scalable Bayes inference and theoretical foundations of high dimensional problems. In particular, I like developing practically efficient methods with strong theoretical support.


 

Email
yyang (at) stat (dot) fsu (dot) edu


Papers

On the Statistical optimality of variational Bayes. 
D. Pati, A. Bhattacharya and Y. Yang
AISTATS, 2018

A Bayesian Approach to Sequential Monitoring of Nonlinear Profiles Using Wavelets [link]
R. Varbanov, E. Chicken, A. Linero and Y. Yang

α-Variational Inference with Statistical Guarantees [arXiv]
Y. Yang, A. Bhattacharya and D. Pati

Frequentist Coverage and Sup-norm Convergence Rate in Gaussian Process Regression [arXiv] 
Y. Yang, A. Bhattacharya and D. Pati

Bayesian Regression Tree Ensembles that Adapt to Smoothness and Sparsity [arXiv] 
A. R. Linero and Y. Yang

Statistical Inference for High-dimensional Regression via Constrained Lasso [arXiv] 
Y. Yang

Information Management for Decentralized Energy Storages under Market Uncertainties [arXiv] 
Q. He, Y. Yang, and B. Zhang

Non-Asymptotic Theory for Nonparametric Testing [arXiv] 
Y. Yang, Z. Shang and G. Cheng

Bayesian Model Selection Consistency and Oracle Inequality with Intractable Marginal Likelihood [arXiv] 
Y. Yang and D. Pati

Bayesian Fractional Posteriors
A. Bhattacharya, D. Pati and Y. Yang
Annals of Statistics, to appear

Communication-Efficient Distributed Statistical Inference
M. I. Jordan, J. D. Lee and Y. Yang
Journal of the American Statistical Association, to appear

Joint Estimation of Quantile Planes over Arbitrary Predictor Spaces [R package]
Y. Yang and S. T. Tokdar
Journal of the American Statistical Association, 2017

Wavelet-Based Bayesian Profile Monitoring
R. Varbanov, E. Chicken, A. Linero and Y. Yang
Proceedings of Industrial and Systems Engineering Research Conference, 2017

On the Computational Complexity of High-Dimensional Bayesian Variable Selection
Y. Yang, M. J. Wainwright and M. I. Jordan
Annals of Statistics, 2016

Randomized Sketches for Kernels: Fast and Optimal Non-Parametric Regression 
Y. Yang, M. Pilanci and M. J. Wainwright
Annals of Statistics, 2017

Semiparametric Bernstein-von Mises Theorem: Second Order Studies [arXiv]
Y. Yang, G. Cheng and D. B. Dunson

Minimax Optimal Bayesian Aggregation [arXiv]
Y. Yang and D. B. Dunson

Minimax Optimal Nonparametric Regression in High Dimensions
Y. Yang and S. T. Tokdar
Annals of Statistics, 2015

Sequential Markov Chain Monte Carlo [arXiv] [C++ code]
Y. Yang and D. B. Dunson

Bayesian Manifold Regression
Y. Yang and D. B. Dunson
Annals of Statistics, 2016

Bayesian Crack Detection in Ultra High Resolution Multimodal Images of Paintings
B. Cornelis, Y. Yang, J. T. Vogelstein, A. Dooms, I. Daubechies and D. B. Dunson
18th International Conference on Digital Signal Processing, 2013

Bayesian Conditional Tensor Factorizations for High-Dimensional Classification [Matlab code]
Y. Yang and D. B. Dunson
Journal of the American Statistical Association, 2016

A Compact Neural Network for Training Support Vector Machines
Y. Yang, Q. He and X. Hu
Neurocomputing, 2012