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A Universal Approximation Theorem for Mixture of Experts Models

A Universal Approximation Theorem for Mixture of Experts Models

11 February 2016
Hien Nguyen
Luke R. Lloyd‐Jones
Geoffrey J. McLachlan
ArXivPDFHTML

Papers citing "A Universal Approximation Theorem for Mixture of Experts Models"

5 / 5 papers shown
Title
Model Selection for Gaussian-gated Gaussian Mixture of Experts Using Dendrograms of Mixing Measures
Model Selection for Gaussian-gated Gaussian Mixture of Experts Using Dendrograms of Mixing Measures
Tuan Thai
TrungTin Nguyen
Dat Do
Nhat Ho
Christopher Drovandi
137
0
0
19 May 2025
A Comprehensive Survey of Mixture-of-Experts: Algorithms, Theory, and Applications
A Comprehensive Survey of Mixture-of-Experts: Algorithms, Theory, and Applications
Siyuan Mu
Sen Lin
MoE
428
5
0
10 Mar 2025
Gradient-free variational learning with conditional mixture networks
Gradient-free variational learning with conditional mixture networks
Conor Heins
Hao Wu
Dimitrije Marković
Alexander Tschantz
Jeff Beck
Christopher L. Buckley
BDL
63
3
0
29 Aug 2024
Functional Mixture Discriminant Analysis with hidden process regression
  for curve classification
Functional Mixture Discriminant Analysis with hidden process regression for curve classification
Faicel Chamroukhi
H. Glotin
Allou Samé
45
22
0
25 Dec 2013
Approximation of conditional densities by smooth mixtures of regressions
Approximation of conditional densities by smooth mixtures of regressions
Andriy Norets
98
25
0
04 Oct 2010
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