Modeling High-Dimensional Data by Combining Simple Experts
Abstract
It is possible to combine multiple non-linear probabilistic models of the same data by multiplying the probability distributions together and then renormalizing. A “productof experts”is a very efficient way to model data that simultaneously satisfies many different constraints. It is difficult to fit a product of experts to data using maximum likelihood because the gradient of the log likelihood is intractable, but there is an efficient way of optimizing a different objective function and this produces good models of high-dimensional data.
Cite
Text
Hinton. "Modeling High-Dimensional Data by Combining Simple Experts." AAAI Conference on Artificial Intelligence, 2000.Markdown
[Hinton. "Modeling High-Dimensional Data by Combining Simple Experts." AAAI Conference on Artificial Intelligence, 2000.](https://mlanthology.org/aaai/2000/hinton2000aaai-modeling/)BibTeX
@inproceedings{hinton2000aaai-modeling,
title = {{Modeling High-Dimensional Data by Combining Simple Experts}},
author = {Hinton, Geoffrey E.},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2000},
pages = {1159-1164},
url = {https://mlanthology.org/aaai/2000/hinton2000aaai-modeling/}
}