Mixture of Partially Linear Experts
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초록

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.

키워드

machine learningmixture of expertsmodel-based clusteringpartially linear modelsROBUST MIXTURESEMIPARAMETRIC MIXTURESREGRESSION-MODELSCENSORED-DATA
제목
Mixture of Partially Linear Experts
저자
Hwang, YeongsanSeo, ByungtaeOh, Sangkon
DOI
10.1002/sta4.70062
발행일
2025-06
유형
Article
저널명
STAT
14
2