Approximations of conditional probability density functions in Lebesgue spaces via mixture of experts models
Abstract Mixture of experts (MoE) models are widely applied for conditional probability density estimation problems. We demonstrate the richness of the class of MoE models by proving denseness results in Lebesgue spaces, when inputs and outputs variables are both compactly supported. We further prov...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2021-08-01
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| Series: | Journal of Statistical Distributions and Applications |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s40488-021-00125-0 |