Chao Gao
Personal Information
I am a Professor of 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 214A, Chicago IL 60637
Email: firstnamelastname@uchicago.edu
Experience & Service
Associate Editor, Annals of Statistics, Sept 2023 -
Site Director, Institute for Data, Econometrics, Algorithms, and Learning (IDEAL), Sept 2022 -
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 -
Computational Lower Bounds for Graphon Estimation via Low-degree Polynomials [arXiv]
Y. Luo and C. Gao
Annals of Statistics, to appear
Minimax Rates in Network Analysis: Graphon Estimation, Community Detection and Hypothesis Testing [arXiv]
C. Gao and Z. Ma
Statistical Science, 2021
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 -
Adaptive Robust Confidence Intervals [arXiv]
Y. Luo and C. Gao
Optimal Estimation of the Null Distribution in Large-Scale Inference [arXiv]
S. Kotekal and C. Gao
Generative Adversarial Nets for Robust Scatter Estimation: A Proper Scoring Rule Perspective [arXiv]
C. Gao, Y. Yao and W. Zhu
Journal of Machine Learning Research, 2020
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, 2020
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 -
Uncertainty Quantification in the Bradley-Terry-Luce Model [arXiv]
C. Gao, Y. Shen and A. Zhang
Information and Inference, 2023
Optimal Full Ranking from Pairwise Comparisons [arXiv]
P. Chen, C. Gao and A. Zhang
Annals of Statistics, 2022
Partial Recovery for Top-k Ranking: Optimality of MLE and Sub-Optimality of Spectral Method [arXiv]
P. Chen, C. Gao and A. Zhang
Annals of Statistics, 2022
Iterative Algorithm for Discrete Structure Recovery [arXiv]
C. Gao and A. Zhang
Annals of Statistics, 2022
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 -
Convergence Rates of Empirical Bayes Posterior Distributions: A Variational Perspective [arXiv]
F. Zhang and C. Gao
Mixing Time of Metropolis-Hastings for Bayesian Community Detection [arXiv]
B. Zhuo and C. Gao
Journal of Machine Learning Research, 2021
Bayesian Model Selection with Graph Structured Sparsity [arXiv]
Y. Kim and C. Gao
Journal of Machine Learning Research, 2020
Convergence Rates of Variational Posterior Distributions [arXiv]
F. Zhang and C. Gao
Annals of Statistics, 2020
A General Framework for Bayes Structured Linear Models [arXiv]
C. Gao, A. van der Vaart and H. Zhou
Annals of Statistics, 2020
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 -
Locally Sharp Goodness-of-Fit Testing in Sup Norm for High-Dimensional Counts [arXiv]
S. Kotekal, J. Chhor and C. Gao
Sharp Phase Transitions in High-Dimensional Changepoint Detection [arXiv]
D. Xiang and C. Gao
Sparsity Meets Correlation in Gaussian Sequence Model [arXiv]
S. Kotekal and C. Gao
Minimax Signal Detection in Sparse Additive Models [arXiv]
S. Kotekal and C. Gao
IEEE Transactions on Information Theory, to appear
Minimax Rates for Sparse Signal Detection under Correlation [arXiv]
S. Kotekal and C. Gao
Information and Inference, 2023
Optimal Orthogonal Group Synchronization and Rotation Group Synchronization [arXiv]
C. Gao and A. Zhang
Information and Inference, 2022
SDP Achieves Exact Minimax Optimality in Phase Synchronization [arXiv]
C. Gao and A. Zhang
IEEE Transactions on Information Theory, 2022
Exact Minimax Estimation for Phase Synchronization [arXiv]
C. Gao and A. Zhang
IEEE Transactions on Information Theory, 2021
Model Repair: Robust Recovery of Over-Parameterized Statistical Models [arXiv]
C. Gao and J. Lafferty
Testing Equivalence of Clustering [arXiv]
C. Gao and Z. Ma
Annals of Statistics, 2022
Minimax Rates in Sparse, High-Dimensional Changepoint Detection [arXiv]
H. Liu, C. Gao and R. Samworth
Annals of Statistics, 2021
Optimal Estimation of Variance in Nonparametric Regression with Random Design [arXiv]
Y. Shen, C. Gao, D. Witten and F. Han
Annals of Statistics, 2020
On Estimation of Isotonic Piecewise Constant Signals [arXiv]
C. Gao, F. Han and C-H. Zhang
Annals of Statistics, 2020
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 of "Network Cross-Validation by Edge Sampling" [oxford]
C. Gao and Z. Ma
Biometrika, 2020
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)
