205 citations · 822 across the 39 of their papers we have counts for
43 papers
Robust Regression with Adaptive Contamination in Response: Optimal Rates and Computational Barriers
Ilias Diakonikolas, Chao Gao, Daniel M. Kane +2
We study robust regression under a contamination model in which covariates are clean while the responses may be corrupted in an adaptive manner. Unlike the classical Huber's contam…
Computational Lower Bounds for Graphon Estimation via Low-degree Polynomials
Yuetian Luo, Chao Gao
Graphon estimation has been one of the most fundamental problems in network analysis and has received considerable attention in the past decade. From the statistical perspective, t…
Sample Average Approximation for Stochastic Optimization with Dependent Data: Performance Guarantees and Tractability
Yafei Wang, Bo Pan, Wei Tu +6
Sample average approximation (SAA), a popular method for tractably solving stochastic optimization problems, enjoys strong asymptotic performance guarantees in settings with indepe…
Uncertainty quantification in the Bradley-Terry-Luce model
Chao Gao, Yandi Shen, Anderson Y. Zhang
The Bradley-Terry-Luce (BTL) model is a benchmark model for pairwise comparisons between individuals. Despite recent progress on the first-order asymptotics of several popular proc…
Optimal Full Ranking from Pairwise Comparisons
Pinhan Chen, Chao Gao, Anderson Y. Zhang
We consider the problem of ranking players from partial pairwise comparison data under the Bradley-Terry-Luce model. For the first time in the literature, the minimax rate of t…
SDP Achieves Exact Minimax Optimality in Phase Synchronization
Chao Gao, Anderson Y. Zhang
We study the phase synchronization problem with noisy measurements , where is an -dimensional complex unit-modulus vector and …
Exact Minimax Estimation for Phase Synchronization
Chao Gao, Anderson Y. Zhang
We study the phase synchronization problem with measurements , where is an -dimensional complex unit-modulus vector and is a c…
Convergence Rates of Empirical Bayes Posterior Distributions: A Variational Perspective
Fengshuo Zhang, Chao Gao
We study the convergence rates of empirical Bayes posterior distributions for nonparametric and high-dimensional inference. We show that as long as the hyperparameter set is discre…
Model Repair: Robust Recovery of Over-Parameterized Statistical Models
Chao Gao, John Lafferty
A new type of robust estimation problem is introduced where the goal is to recover a statistical model that has been corrupted after it has been estimated from data. Methods are pr…
Investigating the relationship between cosmic curvature and dark energy models with the latest supernova sample
Chao Gao, Yun Chen, Jie Zheng
We investigate the relationship between the cosmic curvature and the model of dark energy (hereafter DE) with the recent Type Ia supernovae (hereafter SNe Ia) data, i.e., the Panth…
Iterative Algorithm for Discrete Structure Recovery
Chao Gao, Anderson Y. Zhang
We propose a general modeling and algorithmic framework for discrete structure recovery that can be applied to a wide range of problems. Under this framework, we are able to study…
Testing Equivalence of Clustering
Chao Gao, Zongming Ma
In this paper, we test whether two datasets share a common clustering structure. As a leading example, we focus on comparing clustering structures in two independent random samples…
Minimax rates in sparse, high-dimensional changepoint detection
Haoyang Liu, Chao Gao, Richard J. Samworth
We study the detection of a sparse change in a high-dimensional mean vector as a minimax testing problem. Our first main contribution is to derive the exact minimax testing rate ac…
Generative Adversarial Nets for Robust Scatter Estimation: A Proper Scoring Rule Perspective
Chao Gao, Yuan Yao, Weizhi Zhu
Robust scatter estimation is a fundamental task in statistics. The recent discovery on the connection between robust estimation and generative adversarial nets (GANs) by Gao et al.…
Optimal estimation of variance in nonparametric regression with random design
Yandi Shen, Chao Gao, Daniela Witten +1
Consider the heteroscedastic nonparametric regression model with random design \begin{align*} Y_i = f(X_i) + V^{1/2}(X_i)\varepsilon_i, \quad i=1,2,\ldots,n, \end{align*} with $f(\…
Bayesian Model Selection with Graph Structured Sparsity
Youngseok Kim, Chao Gao
We propose a general algorithmic framework for Bayesian model selection. A spike-and-slab Laplacian prior is introduced to model the underlying structural assumption. Using the not…
Minimax Rates in Network Analysis: Graphon Estimation, Community Detection and Hypothesis Testing
Chao Gao, Zongming Ma
This paper surveys some recent developments in fundamental limits and optimal algorithms for network analysis. We focus on minimax optimal rates in three fundamental problems of ne…
Robust Estimation and Generative Adversarial Nets
Chao Gao, Jiyi Liu, Yuan Yao +1
Robust estimation under Huber's -contamination model has become an important topic in statistics and theoretical computer science. Statistically optimal procedures such as Tukey…
Density Estimation with Contaminated Data: Minimax Rates and Theory of Adaptation
Haoyang Liu, Chao Gao
This paper studies density estimation under pointwise loss in the setting of contamination model. The goal is to estimate at some with i.i.d. observatio…
Convergence Rates of Variational Posterior Distributions
Fengshuo Zhang, Chao Gao
We study convergence rates of variational posterior distributions for nonparametric and high-dimensional inference. We formulate general conditions on prior, likelihood, and variat…
Phase Transitions in Approximate Ranking
Chao Gao
We study the problem of approximate ranking from observations of pairwise interactions. The goal is to estimate the underlying ranks of objects from data through interactions o…
Testing for Global Network Structure Using Small Subgraph Statistics
Chao Gao, John Lafferty
We study the problem of testing for community structure in networks using relations between the observed frequencies of small subgraphs. We propose a simple test for the existence…
Goodness-of-Fit Tests for Random Partitions via Symmetric Polynomials
Chao Gao
We consider goodness-of-fit tests with i.i.d. samples generated from a categorical distribution . For a given , we test the null hypothesis whether $p…
On Estimation of Isotonic Piecewise Constant Signals
Chao Gao, Fang Han, Cun-Hui Zhang
Consider a sequence of real data points with underlying means . This paper starts from studying the setting that is both piecewise cons…