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Rate-optimal graphon estimation
Network analysis is becoming one of the most active research areas in statistics. Significant advances have been made recently on developing theories, methodologies and algorithms for analyzingExpand
Achieving Optimal Misclassification Proportion in Stochastic Block Models
TLDR
A computationally feasible two-stage method that achieves optimal statistical performance in misclassification proportion for stochastic block model under weak regularity conditions and is demonstrated by competitive numerical results. Expand
Sparse CCA: Adaptive Estimation and Computational Barriers
Canonical correlation analysis is a classical technique for exploring the relationship between two sets of variables. It has important applications in analyzing high dimensional datasets originatedExpand
Robust Covariance and Scatter Matrix Estimation under Huber's Contamination Model
Covariance matrix estimation is one of the most important problems in statistics. To accommodate the complexity of modern datasets, it is desired to have estimation procedures that not only canExpand
Convergence rates of variational posterior distributions
We study convergence rates of variational posterior distributions for nonparametric and high-dimensional inference. We formulate general conditions on prior, likelihood, and variational class thatExpand
Sparse CCA via Precision Adjusted Iterative Thresholding
Sparse Canonical Correlation Analysis (CCA) has received considerable attention in high-dimensional data analysis to study the relationship between two sets of random variables. However, there hasExpand
Minimax Optimal Convergence Rates for Estimating Ground Truth from Crowdsourced Labels
Crowdsourcing has become a primary means for label collection in many real-world machine learning applications. A classical method for inferring the true labels from the noisy labels provided byExpand
Exact Exponent in Optimal Rates for Crowdsourcing
TLDR
This paper studies the optimal error rate for aggregating labels provided by a set of non-expert workers under the classic Dawid-Skene model and establishes matching upper and lower bounds with an exact exponent. Expand
Optimal Estimation and Completion of Matrices with Biclustering Structures
TLDR
This paper develops a unified theory for the estimation and completion of matrices with biclustering structures, where the data is a partially observed and noise contaminated data matrix with a certain bic Lustering structure, and shows that a constrained least squares estimator achieves minimax rate-optimal performance in several of the most important scenarios. Expand
Minimax estimation in sparse canonical correlation analysis
Canonical correlation analysis is a widely used multivariate statistical technique for exploring the relation between two sets of variables. This paper considers the problem of estimating the leadingExpand
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