Towards Convergence Rates for Parameter Estimation in Gaussian-gated Mixture of Experts. (arXiv:2305.07572v1 [stat.ML])

Originally introduced as a neural network for ensemble learning, mixture of
experts (MoE) has recently become a fundamental building block of highly
successful modern deep neural networks for heterogeneous data analysis in
several applications, including those in machine learning, statistics,
bioinformatics, economics, and medicine. Despite its popularity in practice, a
satisfactory level of understanding of the convergence behavior of
Gaussian-gated MoE parameter estimation is far from complete. The underlying
reason for this challenge is the inclusion of covariates in the …

analysis applications arxiv become bioinformatics building convergence data data analysis economics ensemble experts machine machine learning medicine mixture of experts moe network networks neural network neural networks statistics