7 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…
A functional tensor model for dynamic multilayer networks with common invariant subspaces and the RKHS estimation
Runshi Tang, Runbing Zheng, Anru R. Zhang +1
Dynamic multilayer networks are frequently used to describe the structure and temporal evolution of multiple relationships among common entities, with applications in fields such a…
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…
A Framework for Computational Lower Bounds in Nontrivial Norm Approximation
Runshi Tang, Yuefeng Han, Anru R. Zhang
In this note, we propose a framework for proving computational lower bounds in norm approximation by leveraging a reverse detection--estimation gap. The starting point is a testing…
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…
Tensor Decomposition with Unaligned Observations
Runshi Tang, Tamara Kolda, Anru R. Zhang
This paper presents a canonical polyadic (CP) tensor decomposition that addresses unaligned observations. The mode with unaligned observations is represented using functions in a r…