5 citations · 13 across the 4 of their papers we have counts for
5 papers
Linear Regression Beyond Covariance: Latent Slope Spectra from Higher-Order Cumulants
Anirban Nath, Ming Yuan
Least squares summarizes the joint distribution of a response and regressor through second-order information. When an observed regressor is composed of latent components carrying d…
On the Multiway Principal Component Analysis
Jialin Ouyang, Ming Yuan
Multiway data are becoming more and more common. While there are many approaches to extending principal component analysis (PCA) from usual data matrices to multiway arrays, their…
Higher-order least squares: assessing partial goodness of fit of linear causal models
Christoph Schultheiss, Peter Bühlmann, Ming Yuan
We introduce a simple diagnostic test for assessing the overall or partial goodness of fit of a linear causal model with errors being independent of the covariates. In particular,…
Perturbation Bounds for (Nearly) Orthogonally Decomposable Tensors
Arnab Auddy, Ming Yuan
We develop deterministic perturbation bounds for singular values and vectors of orthogonally decomposable tensors, in a spirit similar to classical results for matrices such as tho…
Incoherent Tensor Norms and Their Applications in Higher Order Tensor Completion
Ming Yuan, Cun-Hui Zhang
In this paper, we investigate the sample size requirement for a general class of nuclear norm minimization methods for higher order tensor completion. We introduce a class of tenso…