# Chao Gao

**Personal Information**

I am an assistant professor in statistics at University of Chicago. I graduated from Yale University. My advisor is Harry Zhou. My research lies in nonparametric and high-dimensional statistics, network analysis, Bayes theory and robust statistics.

**Contact**

Address: 5747 S Ellis Ave, Jones 314, Chicago IL 60637

Email: firstnamelastname@galton.uchicago.edu

**Experience & Service**

Associate Editor, Bernoulli, Jan 2019 -

Associate Editor, Electronic Journal of Statistics, Mar 2017 -

Visiting Student at Leiden University (Prof. Aad van der Vaart), Jan 2015 - May 2015

Intern at Microsoft Research Redmond, May 2014 - Aug 2014

Intern at Microsoft Research Redmond, May 2013 - Aug 2013

**Papers**

**- Network Analysis -**

**Minimax Rates in Network Analysis: Graphon Estimation, Community Detection and Hypothesis Testing** [arXiv]

C. Gao and Z. Ma

Statistical Science, to appear

**Testing for Global Network Structure Using Small Subgraph Statistics** [arXiv]

C. Gao and J. Lafferty

**Testing Network Structure Using Relations Between Small Subgraph Probabilities** [arXiv]

C. Gao and J. Lafferty

**Community Detection in Degree-Corrected Block Models** [arXiv]

C. Gao, Z. Ma, A. Zhang and H. Zhou

Annals of Statistics, 2018

**Achieving Optimal Misclassification Proportion in Stochastic Block Model** [arXiv]

C. Gao, Z. Ma, A. Zhang and H. Zhou

Journal of Machine Learning Research, 2017

**Rate-Optimal Graphon Estimation** [arXiv]

C. Gao, Y. Lu and H. Zhou

Annals of Statistics, 2015

**Optimal Estimation and Completion of Matrices with Biclustering Structures** [arXiv]

C. Gao, Y. Lu, Z. Ma and H. Zhou

Journal of Machine Learning Research, 2016

**- Robust Statistics -**

**Generative Adversarial Nets for Robust Scatter Estimation: A Proper Scoring Rule Perspective** [arXiv]

C. Gao, Y. Yao and W. Zhu

**Robust Estimation and Generative Adversarial Nets** [arXiv]

C. Gao, J. Liu, Y. Yao and W. Zhu

ICLR, 2019

**Density Estimation with Contaminated Data: Minimax Rates and Theory of Adaptation** [arXiv]

H. Liu and C. Gao

Electronic Journal of Statistics, 2019

**Robust Regression via Mutivariate Regression Depth** [arXiv]

C. Gao

Bernoulli, to appear

**Robust Covariance Matrix Estimation under Huber’s Contamination Model** [arXiv]

M. Chen, C. Gao and Z. Ren

Annals of Statistics, 2018

**A General Decision Theory for Huber's $\epsilon$-Contamination Model** [arXiv]

M. Chen, C. Gao and Z. Ren

Electronic Journal of Statistics, 2016

**- Ranking and Permutation -**

**Iterative Algorithm for Discrete Structure Recovery** [arXiv]

C. Gao and A. Zhang

**Phase Transitions in Approximate Ranking** [arXiv]

C. Gao

**Goodness-of-Fit Tests for Random Partitions via Symmetric Polynomials** [arXiv]

C. Gao

Journal of Machine Learning Research, 2018

**- Bayes Theory -**

**Bayesian Model Selection with Graph Structured Sparsity** [arXiv]

Y. Kim and C. Gao

**Mixing Time of Metropolis-Hastings for Bayesian Community Detection** [arXiv]

B. Zhuo and C. Gao

**Convergence Rates of Variational Posterior Distributions** [arXiv]

F. Zhang and C. Gao

Annals of Statistics, to appear

**A General Framework for Bayes Structured Linear Models** [arXiv]

C. Gao, A. van der Vaart and H. Zhou

Annals of Statistics, to appear

**Rate-optimal Posterior Contraction for Sparse PCA** [arXiv]

C. Gao and H. Zhou

Annals of Statistics, 2015

**Rate Exact Bayesian Adaptation with Modified Block Priors** [arXiv]

C. Gao and H. Zhou

Annals of Statistics, 2016

**Bernstein-von Mises Theorems for Functionals of the Covariance Matrix** [arXiv]

C. Gao and H. Zhou

Electronic Journal of Statistics, 2016

**Posterior Contraction Rates of Phylogenetic Indian Buffet Processes** [arXiv]

M. Chen, C. Gao and H. Zhao

Bayesian Analysis, 2016

**- High Dimensional Statistics -**

**Testing Equivalence of Clustering** [arXiv]

C. Gao and Z. Ma

**Minimax Rates in Sparse, High-Dimensional Changepoint Detection** [arXiv]

H. Liu, C. Gao and R. Samworth

**Optimal Estimation of Variance in Nonparametric Regression with Random Design** [arXiv]

Y. Shen, C. Gao, D. Witten and F. Han

**On Estimation of Isotonic Piecewise Constant Signals** [arXiv]

C. Gao, F. Han and C-H. Zhang

Annals of Statistics, to appear

**Stochastic Canonical Correlation Analysis** [arXiv]

C. Gao, D. Garber, N. Srebro, J. Wang and W. Wang

Journal of Machine Learning Research, 2019

**Sparse CCA: Adaptive Estimation and Computational Barriers** [arXiv]

C. Gao, Z. Ma and H. Zhou

Annals of Statistics, 2017

**Minimax Estimation in Sparse Canonical Correlation Analysis** [arXiv]

C. Gao, Z. Ma, Z. Ren and H. Zhou

Annals of Statistics, 2015

**Sparse CCA via Precision Adjusted Iterative Thresholding** [arXiv]

M. Chen, C. Gao, Z. Ren and H. Zhou

**Exact Exponent in Optimal Rates for Crowdsourcing** [arXiv]

C. Gao Y. Lu and D. Zhou

ICML, 2016

**Minimax Optimal Convergence Rates for Estimating Ground Truth from Crowdsourced Labels** [arXiv]

C. Gao and D. Zhou

**- Others -**

**Discussion on "Sparse Graphs using Exchangeable Random Measures"** [wiley]

C. Gao

Journal of the Royal Statistical Society: Series B, 2017

**Detecting the Impact Area of BP Deepwater Horizon Oil Discharge: An Analysis by Time Varying Coefficient Logistic Models and Boosted Trees** [spinger]

T. Li, C. Gao, M. Xu and B. Rajaratnam

Computational Statistics, 2014 (Winner of 2011 ASA Data Expo)