# Parsimonious Mixtures of Skewed Bilinear Factor Analyzers

arXiv: https://arxiv.org/abs/2607.14297 · HTML: https://mlsanity.com/paper/2607.14297/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 9 of its 34 references that are in the map.
- First posted on arXiv 15 Jul 2026.

## Builds on (most cited first, 9 of 9)

- [A Mixture of Generalized Hyperbolic Distributions](https://mlsanity.com/paper/1305.1036/) (2013)
- [Capturing Patterns via Parsimonious t Mixture Models](https://mlsanity.com/paper/1303.2316/) (2013)
- [Finite Mixtures of Skewed Matrix Variate Distributions](https://mlsanity.com/paper/1703.08882/) (2017)
- [Flexible Clustering for High-Dimensional Data via Mixtures of Joint Generalized Hyperbolic Models](https://mlsanity.com/paper/1705.03130/) (2017)
- [Hidden Truncation Hyperbolic Distributions, Finite Mixtures Thereof, and Their Application for Clustering](https://mlsanity.com/paper/1707.02247/) (2017)
- [A Mixture of Matrix Variate Bilinear Factor Analyzers](https://mlsanity.com/paper/1712.08664/) (2017)
- [Three Skewed Matrix Variate Distributions](https://mlsanity.com/paper/1704.02531/) (2017)
- [Mixtures of Skewed Matrix Variate Bilinear Factor Analyzers](https://mlsanity.com/paper/1809.02385/) (2018)
- [Parsimonious Mixtures of Matrix Variate Bilinear Factor Analyzers](https://mlsanity.com/paper/1911.09012/) (2019)

## Abstract (arXiv)

Mixture models which cluster skewed random matrices can often suffer from over-parameterization in the absence of performing dimension reduction. Even with the use of bilinear factor analyzers, further parameter reduction can be achieved by constraining parameters over clusters. In this manuscript propose a parsimonious family of 256 models for mixtures of skewed matrix variate bilinear factor analyzers, specifically in the case of the skew t distribution. An AECM algorithm for parameter estimation is discussed in detail. Further, extensive simulations are performed, and the method is considered in the case of the MNIST dataset and the Olivetti faces dataset.