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- Product_of_experts abstract "Product of experts (PoE) is a machine learning technique. It models a probability distribution by combining the output from several simpler distributions.It was proposed by Geoff Hinton, along with an algorithm for training the parameters of such a system.The core idea is to combine several probability distributions ("experts") by multiplying their density functions—making the PoE classification similar to an "and" operation. This allows each expert to make decisions on the basis of a few dimensions without having to cover the full dimensionality of a problem.This is related to (but quite different from) a mixture model, where several probability distributions are combined via an "or" operation, which is a weighted sum of their density functions.".
- Product_of_experts wikiPageID "24825162".
- Product_of_experts wikiPageRevisionID "508558707".
- Product_of_experts hasPhotoCollection Product_of_experts.
- Product_of_experts subject Category:Machine_learning.
- Product_of_experts comment "Product of experts (PoE) is a machine learning technique. It models a probability distribution by combining the output from several simpler distributions.It was proposed by Geoff Hinton, along with an algorithm for training the parameters of such a system.The core idea is to combine several probability distributions ("experts") by multiplying their density functions—making the PoE classification similar to an "and" operation.".
- Product_of_experts label "Product of experts".
- Product_of_experts sameAs m.080ncz3.
- Product_of_experts sameAs Q7247781.
- Product_of_experts sameAs Q7247781.
- Product_of_experts wasDerivedFrom Product_of_experts?oldid=508558707.
- Product_of_experts isPrimaryTopicOf Product_of_experts.