Yun Yang

Biography

I joined the Statistics Department at University of Illinois Urbana-Champaign in 2018. I was an Assistant Professor in the Statistics Department at Florida State University from 2016 to 2018. 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.

Contact

Email: yy84 (at) illinois (dot) edu

Office: 104F, Illini Hall, 725 S. Wright St., Champaign, IL 61820


Teaching

2021 Fall, STAT 511: Advanced Mathematical Statistics

2021 Spring, STAT 410: Statistics and Probability II

2020 Fall, STAT 510: Mathematical Statistics I

2020 Spring, STAT 510: Mathematical Statistics

2019 Fall, STAT 510: Mathematical Statistics I

2019 Spring, STAT 424: Analysis of Variance

2019 Spring, STAT 410: Statistics and Probability II


Publications

(* indicates students)

Skyformer: Remodel Self-Attention with Gaussian Kernel and Nystrom Method.

Y. Chen*, Q. Zeng*, H. Ji and Y. Yang

Conference on Neural Information Processing Systems (NeurIPS), 2021


Regret Lower Bound and Optimal Algorithm for High-Dimensional Contextual Linear Bandit. [arXiv]

K. Li*, Y. Yang and N. Narisetty

Electronic Journal of Statistics, to appear


On Empirical Bayes Variational Autoencoder: An Excess Risk Bound.

R. Tang* and Y. Yang

Conference on Learning Theory (COLT), 2021


Cutoff for Exact Recovery of Gaussian Mixture Models.

X. Chen and Y. Yang

IEEE Transactions on Information Theory, 2021


Distributed Estimation for Principal Component Analysis: an Enlarged Eigenspace Analysis.

X. Chen, J. Lee, H. Li* and Y. Yang

Journal of the American Statistical Association, 2021


Diffusion K-means Clustering on Manifolds: Provable Exact Recovery via Semidefinite Relaxations.

X. Chen and Y. Yang

Applied and Computational Harmonic Analysis, 2021


Hanson-Wright Inequality in Hilbert Spaces with Application to K-means Clustering for Non-Euclidean Data.

X. Chen and Y. Yang

Bernoulli, 2021


Nonparametric Testing under Randomized Sketching.

M. Liu, Z. Shang, Y. Yang and G. Cheng

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021


Beyond Rebalancing: Crowd-Sourcing and Geo-Fencing for Shared-Mobility Systems.

Q. He, T. Nie, Y. Yang and Z. Shen

Production and Operations Management, 2021


Accumulations of Projections—A Unified Framework for Random Sketches in Kernel Ridge Regression.

Y. Chen* and Y. Yang

Artificial Intelligence and Statistics Conference (AISTATS), 2021


Fast Statistical Leverage Score Approximation in Kernel Ridge Regression.

Y. Chen* and Y. Yang

Artificial Intelligence and Statistics Conference (AISTATS), 2021


α-variational Inference with Statistical Guarantees.

Y. Yang, A. Bhattacharya and D. Pati

Annals of Statistics, 2020


Computationally Efficient Bayesian Sequential Function Monitoring.

W. Shamp*, R. Varbanov*, E. Chicken, A. Linero and Y. Yang

Journal of Quality Technology, 2020


Non-asymptotic Analysis for Nonparametric Testing.

Y. Yang, Z. Shang and G. Cheng

Conference on Learning Theory (COLT), 2020


Bayesian Fractional Posteriors.

A. Bhattacharya, D. Pati and Y. Yang

Annals of Statistics, 2019


Smart Energy Storage Management via Information Systems Design.

Q. He, Y. Yang, Q. Bai and B. Zhang

Energy Economics, 2019


A Bayesian Approach to Sequential Monitoring of Nonlinear Profiles Using Wavelets.

R. Varbanov*, E. Chicken, A. Linero and Y. Yang

Quality and Reliability Engineering International, 2019


Communication-Efficient Distributed Statistical Inference.

M. I. Jordan, J. D. Lee and Y. Yang

Journal of the American Statistical Association, 2018


Bayesian Regression Tree Ensembles that Adapt to Smoothness and Sparsity.

A. R. Linero and Y. Yang

Journal of the Royal Statistical Society: Series B, 2018


On the Statistical Optimality of Variational Bayes.

D. Pati, A. Bhattacharya and Y. Yang

Artificial Intelligence and Statistics Conference (AISTATS), 2018


Joint Estimation of Quantile Planes over Arbitrary Predictor Spaces [R package]

Y. Yang and S. T. Tokdar

Journal of the American Statistical Association, 2017


Randomized Sketches for Kernels: Fast and Optimal Non-Parametric Regression.

Y. Yang, M. Pilanci and M. J. Wainwright

Annals of Statistics, 2017


Wavelet-Based Bayesian Profile Monitoring.

R. Varbanov*, E. Chicken, A. Linero and Y. Yang

Industrial and Systems Engineering Research Conference (ISERC), 2017


On the Computational Complexity of High-Dimensional Bayesian Variable Selection.

Y. Yang, M. J. Wainwright and M. I. Jordan

Annals of Statistics, 2016


Bayesian Manifold Regression.

Y. Yang and D. B. Dunson

Annals of Statistics, 2016


Bayesian Conditional Tensor Factorizations for High-Dimensional Classification [Matlab code]

Y. Yang and D. B. Dunson

Journal of the American Statistical Association, 2016


Minimax Optimal Nonparametric Regression in High Dimensions.

Y. Yang and S. T. Tokdar

Annals of Statistics, 2015


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

International Conference on Digital Signal Processing (ICDSP), 2013


A Compact Neural Network for Training Support Vector Machines.

Y. Yang, Q. He and X. Hu

Neurocomputing, 2012



Manuscripts

(* indicates students)

Learning Topic Models: Identifiability and Finite-Sample Analysis [arXiv]
Y. Chen*, S. He*, Y. Yang and F. Liang


Statistical Inference for Bayesian Risk Minimization via Exponentially Tilted Empirical Likelihood [arXiv]
R. Tang* and Y. Yang


Statistical Inference in Mean-Field Variational Bayes [arXiv]

H. Wei* and Y. Yang


Implicit Regularization via Hadamard Product Over-Parametrization in High-Dimensional Linear Regression [arXiv]

P. Zhao*, Y. Yang and Q. He


Gaussian Processes with Errors in Variables: Theory and Computation [arXiv]

S. Zhou*, D. Pati, T. Wang, Y. Yang and R. J. Carroll


Model-based Statistical Depth with Applications to Functional Data [arXiv]

W. Zhao*, Z. Xu*, Y. Yang and W. Wu


Frequentist Coverage and Sup-norm Convergence Rate in Gaussian Process Regression [arXiv]

Y. Yang, A. Bhattacharya and D. Pati


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

Y. Yang


Bayesian Model Selection Consistency and Oracle Inequality with Intractable Marginal Likelihood [arXiv]

Y. Yang and D. Pati


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


Sequential Markov Chain Monte Carlo [arXiv] [C++ code]

Y. Yang and D. B. Dunson