We provide a theoretical treatment of over-specified Gaussian mixtures of experts with covariate-free gating networks. We establish the convergence rates of the ...
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Jul 9, 2019 · Abstract:We provide a theoretical treatment of over-specified Gaussian mixtures of experts with covariate-free gating networks.
We provide a theoretical treatment of over-specified Gaussian mixtures of experts with covariate-free gating networks. We establish the convergence rates of ...
We provide a theoretical treatment of over-specified Gaussian mixtures of experts with covariate-free gating networks. We establish the convergence rates of ...
Towards Convergence Rates for Parameter Estimation in Gaussian-gated Mixture of Experts · Computer Science, Mathematics. AISTATS · 2024.
We provide a theoretical treatment of over-specified Gaussian mixtures of experts with covariate-free gating networks. We establish the convergence rates of ...
May 12, 2023 · We provide a convergence analysis for maximum likelihood estimation (MLE) in the Gaussian-gated MoE model.
Apr 1, 2023 · Towards Convergence Rates for Parameter Estimation in Gaussian-gated Mixture of Experts · Originally introduced as a neural network for ...
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In this paper, we conduct a convergence analysis for density estimation and parameter estimation in the. Gaussian-gated mixture of experts (GMoE) under two.
The convergence rate is found to be dependent on both $m$ and $k$, and certain choices of $m$ and $k$ are found to produce optimal convergence rates. Therefore, ...