18 citations · 23 across the 6 of their papers we have counts for
7 papers
Heteroskedastic Canonical Polyadic Tensor Decomposition
Kyle Ritscher, Carlos Llosa-Vite
When minimizing the squared-error loss, the popular CP decomposition can be interpreted as parameter inference in a Gaussian model with a low-rank mean tensor and constant variance…
A Latent-Variable Formulation of the Poisson Canonical Polyadic Tensor Model: Maximum Likelihood Estimation and Fisher Information
Carlos Llosa-Vite, Daniel M. Dunlavy, Richard B. Lehoucq +2
We establish parameter inference for the Poisson canonical polyadic (PCP) model of tensor count data through a latent-variable formulation. Our approach exploits the property that…
Near-Efficient and Non-Asymptotic Multiway Inference
Oscar López, Arvind Prasadan, Carlos Llosa-Vite +2
We establish non-asymptotic efficiency guarantees for tensor decomposition-based inference in count data models. Under a Poisson framework, we consider two related goals: (i) param…
The Average Spectrum Norm and Near-Optimal Tensor Completion
Oscar López, Richard Lehoucq, Carlos Llosa-Vite +2
We introduce a new tensor norm, the average spectrum norm, to study sample complexity of tensor completion problems based on the canonical polyadic decomposition (CPD). Properties…
Elliptically-Contoured Tensor-variate Distributions with Application to Improved Image Learning
Carlos Llosa-Vite, Ranjan Maitra
Statistical analysis of tensor-valued data has largely used the tensor-variate normal (TVN) distribution that may be inadequate when data comes from distributions with heavier or l…
Quantitative Matching of Forensic Evidence Fragments Utilizing 3D Microscopy Analysis of Fracture Surface Replicas
Bishoy Dawood, Carlos Llosa-Vite, Geoffrey Z. Thompson +6
Fractured surfaces carry unique details that can provide an accurate quantitative comparison to support comparative forensic analysis of those fractured surfaces. In this study, a…
Reduced-Rank Tensor-on-Tensor Regression and Tensor-variate Analysis of Variance
Carlos Llosa-Vite, Ranjan Maitra
Fitting regression models with many multivariate responses and covariates can be challenging, but such responses and covariates sometimes have tensor-variate structure. We extend t…