4 citations · 4 across the 5 of their papers we have counts for
5 papers
An efficient EM algorithm for both element-wise and structural missingness in matrix-variate normal mixture models
Hanzhang Lu, Jeffrey L. Andrews, Ryan P. Browne
Matrix-variate data with missing entries arise frequently in applications where observations are naturally organized as two-dimensional arrays. Although the matrix normal distribut…
Robust model-based clustering via mixtures of multivariate pseudo-Voigt distributions
Babak F. Dehkordi, Jeffrey L. Andrews, Andrew Jirasek
We propose a multivariate extension of the pseudo-Voigt profile-a weighted convex combination of Gaussian and Cauchy distributions-within a finite mixture modeling framework for ro…
Statistical inference for sketching algorithms
R. P. Browne, J. L. Andrews
Sketching algorithms use random projections to generate a smaller sketched data set, often for the purposes of modelling. Complete and partial sketch regression estimates can be co…
Nonnegative Matrix Factorization with Group and Basis Restrictions
Phillip Shreeves, Jeffrey L. Andrews, Xinchen Deng +2
Nonnegative matrix factorization (NMF) is a popular method used to reduce dimensionality in data sets whose elements are nonnegative. It does so by decomposing the data set of inte…
Variable Selection for Clustering and Classification
Jeffrey L. Andrews, Paul D. McNicholas
As data sets continue to grow in size and complexity, effective and efficient techniques are needed to target important features in the variable space. Many of the variable selecti…