3 papers
stat.ML2026
Model Selection and Parameter Estimation for Multidimensional Gaussian Mixture Models with a Common Covariance Matrix
Xinyu Liu, Hai Zhang
We study model-order selection and component-mean estimation for multidimensional Gaussian mixture models with a known common covariance matrix. Using empirical characteristic-func…
stat.ML2024
Model Selection and Parameter Estimation of One-Dimensional Gaussian Mixture Models
Xinyu Liu, Hai Zhang
In this paper, we study the problem of learning one-dimensional Gaussian mixture models (GMMs) with a specific focus on estimating both the model order and the mixing distribution…
cs.LG2024
A Structure-Guided Gauss-Newton Method for Shallow ReLU Neural Network
Zhiqiang Cai, Tong Ding, Min Liu +2
In this paper, we propose a structure-guided Gauss-Newton (SgGN) method for solving least squares problems using a shallow ReLU neural network. The method effectively takes advanta…