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Hier finden Sie wissenschaftliche Publikationen aus den FraunhoferInstituten. Maximum entropy PDF projection: A review
 Verdoolaege, G. ; American Institute of Physics AIP, New York: Bayesian inference and maximum entropy methods in science and engineering : Proceedings of the 36th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering (MaxEnt 2016), 1015 July 2016, Ghent, Belgium New York, N.Y.: AIP Press, 2017 (AIP Conference Proceedings 1853) ISBN: 9780735415270 Art. 070001 
 International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering (MaxEnt) <36, 2016, Ghent> 

 English 
 Conference Paper 
 Fraunhofer FKIE () 
Abstract
We review maximum entropy (MaxEnt) PDF projection, a method with wide potential applications in statistical inference. The method constructs a sampling distribution for a highdimensional vector x based on knowing the sampling distribution p(z) of a lowerdimensional feature z = T (x). Under mild conditions, the distribution p(x) having highest possible entropy among all distributions consistent with p(z) may be readily found. Furthermore, the MaxEnt p(x) may be sampled, making the approach useful in Monte Carlo methods. We review the theorem and present a case study in model order selection and classification for handwritten character recognition.