DATA PROCESSING AND ANALYSIS
INTELLIGENCE SYSTEMS AND TECHNOLOGIES
MATHEMATICAL MODELING
Y. S. Popkov On Some Properties of Randomized Machine Learning Procedures in the Presence of Noisy Data
MANAGEMENT AND DECISION MAKING
MATHEMATICAL FOUNDATIONS OF INFORMATION TECHNOLOGY
Y. S. Popkov On Some Properties of Randomized Machine Learning Procedures in the Presence of Noisy Data
Abstract. 

We study various models of measuring noises in the procedures of randomized entropy estimation of probability density functions: additive and multiplicative, measuring noises at the input and output of the object’s model. The properties of entropy-optimal probability density functions are studied, it is shown that the measurement noises corresponding to them are heteroscedastic.

Keywords: 

entropy estimation, density functions, Lagrange multipliers, heteroscedastic noise, variation models.

PP. 89-95.

DOI 10.14357/20718632230209
 
References

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