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