Year: 2025
Type: article
Abstract: ABSTRACT The mixture of experts framework is widely used in machine learning to model data with latent clusters. However, the conventional assumption of linearity between response variables and covariates may overlook inherent nonlinear relationships, potentially yielding suboptimal estimates. To overcome this limitation, we propose a partially linear structure that incorporates unspecified functions to capture nonlinear relationships. We establish the identifiability of the proposed model under mild conditions and introduce a practical estimation algorithm. We present the performance of our approach through numerical studies, including simulations and real data analysis.
Source: Stat
DOI: 10.1002/sta4.70062
Authors: Yeongsan Hwang, Byungtae Seo, Sangkon Oh
Institutions: Sungkyunkwan University, Pukyong National University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,610
OpenAlex ID: W4409483592