Integration of Stochastic Models by Minimizing -Divergence

@article{Amari2007IntegrationOS,
  title={Integration of Stochastic Models by Minimizing -Divergence},
  author={Shun-ichi Amari},
  journal={Neural Computation},
  year={2007},
  volume={19},
  pages={2780-2796}
}
When there are a number of stochastic models in the form of probability distributions, one needs to integrate them. Mixtures of distributions are frequently used, but exponential mixtures also provide a good means of integration. This letter proposes a one-parameter family of integration, called -integration, which includes all of these well-known integrations. These are generalizations of various averages of numbers such as arithmetic, geometric, and harmonic averages. There are psychophysical… CONTINUE READING
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