5 papers
Bandable Cumulant Tensors: Optimal Estimation and Applications in Non-Gaussian Data Modeling
Runshi Tang, Anru R. Zhang, Yuefeng Han +1
Higher-order cumulants capture the non-Gaussian dependence that covariance misses, but they are hard to use in high dimensions. An order- cumulant tensor has entries, and…
Optimal Estimation of Discrete Multiview Distributions under Heteroskedastic Multinomial Sampling
Runshi Tang, Julien Chhor, Olga Klopp +2
Multiview latent-variable models provide a fundamental framework for discrete data analysis, with applications to latent structure models, topic models, and mixtures of product dis…
From Reverse Detection--Estimation Gaps to Computational Lower Bounds for Norm Approximation
Runshi Tang, Yuefeng Han, Anru R. Zhang
We develop a general reduction scheme that converts reverse detection--estimation gaps into computational lower bounds for norm approximation. If an efficiently computable estimato…
Detection Is Harder Than Estimation in Certain Regimes: Inference for Moment and Cumulant Tensors
Runshi Tang, Yuefeng Han, Anru R. Zhang
We study estimation and detection of high-order moment and cumulant tensors from i.i.d.\ observations of a -dimensional random vector, with performance measured in tensor sp…
Statistical Inference for Low-Rank Tensors: Heteroskedasticity, Subgaussianity, and Applications
Joshua Agterberg, Anru Zhang
In this paper, we consider inference and uncertainty quantification for low Tucker rank tensors with additive noise in the high-dimensional regime. Focusing on the output of the hi…