160 citations · 679 across the 27 of their papers we have counts for
27 papers
Maximum of sparsely equicorrelated Gaussian fields and applications
Johannes Heiny, Tiefeng Jiang, Tuan Pham +1
We investigate the extreme values of a sparse and equicorrelated Gaussian field on a triangle: the correlations on every vertical or horizontal line are all equal to a parameter $r…
Asymptotic Distributions of Largest Pearson Correlation Coefficients under Dependent Structures
Tiefeng Jiang, Tuan Pham
Given a random sample from a multivariate normal distribution whose covariance matrix is a Toeplitz matrix, we study the largest off-diagonal entry of the sample correlation matrix…
Non-Asymptotic Analysis of Online Multiplicative Stochastic Gradient Descent
Riddhiman Bhattacharya, Tiefeng Jiang
Past research has indicated that the covariance of the Stochastic Gradient Descent (SGD) error done via minibatching plays a critical role in determining its regularization and esc…
Mean Test with Fewer Observation than Dimension and Ratio Unbiased Estimator for Correlation Matrix
Tiefeng Jiang, Ping Li
Hotelling's T-squared test is a classical tool to test if the normal mean of a multivariate normal distribution is a specified one or the means of two multivariate normal means are…
Contiguity under high dimensional Gaussianity with applications to covariance testing
Qiyang Han, Tiefeng Jiang, Yandi Shen
Le Cam's third/contiguity lemma is a fundamental probabilistic tool to compute the limiting distribution of a given statistic under a non-null sequence of probability measure…
Max-sum tests for cross-sectional dependence of high-demensional panel data
Long Feng, Tiefeng Jiang, Binghui Liu +1
We consider a testing problem for cross-sectional dependence for high-dimensional panel data, where the number of cross-sectional units is potentially much larger than the number o…