205 citations · 822 across the 39 of their papers we have counts for
9 papers · 1 filter
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…
Testing Network Structure Using Relations Between Small Subgraph Probabilities
Chao Gao, John Lafferty
We study the problem of testing for structure in networks using relations between the observed frequencies of small subgraphs. We consider the statistics \begin{align*} T_3 & =(\te…
Robust Regression via Mutivariate Regression Depth
Chao Gao
This paper studies robust regression in the settings of Huber's -contamination models. We consider estimators that are maximizers of multivariate regression depth functions. The…
Stochastic Canonical Correlation Analysis
Chao Gao, Dan Garber, Nathan Srebro +2
We study the sample complexity of canonical correlation analysis (CCA), \ie, the number of samples needed to estimate the population canonical correlation and directions up to arbi…