Results 71 to 80 of about 2,896,920 (185)

Perfect Probability Measures and Regular Conditional Probabilities

The Annals of Mathematical Statistics, 1966
In an attempt to refine the axiomatic model of a probability space introduced by Kolmogorov [11], Gnendenko and Kolmogorov [5] introduced the concept of a perfect probability measure. The desirability of some sort of refinement has been pointed out by several well known examples [2], [3], [8], which display a certain amount of pathology inherent in ...
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Unsupervised Domain Adaptation Method Based on Relative Entropy Regularization and Measure Propagation

Entropy
This paper presents a novel unsupervised domain adaptation (UDA) framework that integrates information-theoretic principles to mitigate distributional discrepancies between source and target domains.
Lianghao Tan, Zhuo Peng, Yongjia Song, Xiaoyi Liu, Huangqi Jiang, Shubing Liu, Weixi Wu, Zhiyuan Xiang   +7 more
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Probability via Expectation Measures

Entropy
Since the seminal work of Kolmogorov, probability theory has been based on measure theory, where the central components are so-called probability measures, defined as measures with total mass equal to 1. In Kolmogorov’s theory, a probability measure is used to model an experiment with a single outcome that will belong to exactly one out of several ...
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Conditional Quantization for Uniform Distributions on Line Segments and Regular Polygons

Mathematics
Quantization for a Borel probability measure refers to the idea of estimating a given probability by a discrete probability with support containing a finite number of elements.
Pigar Biteng, Mathieu Caguiat, Tsianna Dominguez, Mrinal Kanti Roychowdhury   +3 more
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Completeness theorem for probability models with finitely many valued measure

Open Mathematics, 2019
The aim of the paper is to prove the completeness theorem for probability models with finitely many valued measure.
Rašković Miodrag, Djordjević Radosav, Stojanović Nenad   +2 more
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On the degree of uniformity measure for probability distributions

Journal of Physics Communications
A key challenge in studying probability distributions is quantifying the inherent inequality within them. Certain parts of the distribution have higher probabilities than others, and our goal is to measure this inequality using the concept of ...
R Rajaram, N Ritchey, B Castellani
doaj   +1 more source

Object Tracking Using Local Multiple Features and a Posterior Probability Measure. [PDF]

Sensors (Basel), 2017
Guo W, Feng Z, Ren X.
europepmc   +1 more source

An Inverse Problem for a Class of Conditional Probability Measure-Dependent Evolution Equations. [PDF]

Inverse Probl, 2016
Mirzaev I, Byrne EC, Bortz DM.
europepmc   +1 more source

On invariant probability measures I [PDF]

Pacific Journal of Mathematics, 1960
Blum, J. R., Hanson, D. L.
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Variations on the Expectation Due to Changes in the Probability Measure. [PDF]

Entropy (Basel)
Perlaza SM, Bisson G.
europepmc   +1 more source