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Open Quantum Systems Decoherence
Quantum Machine Learning
Update of prior probabilities by minimal divergence
arXiv
Authors: Jan Naudts
Year
2019
Paper ID
15114
Status
Preprint
Abstract Read
~2 min
Abstract Words
54
Citations
N/A
Abstract
The present paper investigates the update of an empirical probability distribution with the results of a new set of observations. The optimal update is obtained by minimizing either the Hellinger distance or the quadratic Bregman divergence. The results obtained by the two methods differ. Updates with information about conditional probabilities are considered as well.
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- This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
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- The present paper investigates the update of an empirical probability distribution with the results of a new set of observations.
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