Randomization and entropy in machine learning and data processing

DOI10.1134/S1064562422030073OpenAlexW4289883777MaRDI QIDQ2171640

Yuri S. Popkov

Publication date: 9 September 2022

Published in: Doklady Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1134/s1064562422030073

zbMATH Keywords

entropyclassificationclusteringrandomizationbalance equationsmachine learningdata processingestimates of conditional maximum entropygeneration of random ensemblesparametrization of models

Mathematics Subject Classification ID

Artificial intelligence (68Txx) Computer science (68-XX) Communication, information (94Axx)

Related Items (1)

Randomized machine learning algorithms to forecast the evolution of thermokarst lakes area in permafrost zones

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• A Mathematical Theory of Communication
• Data mining. Concepts and techniques
• Experimental comparison fo cluster analysis of algorithms
• On calibration error of randomized forecasting algorithms
• Renyi entropy as a statistical entropy for complex systems
• Papers on probability, statistics and statistical physics. Ed. by R. D. Rosenkrantz.
• Entropy dimension reduction method for randomized machine learning problems
• Principal component analysis.
• Macrosystems theory and its applications. Equilibrium models
• Asymptotic efficiency of maximum entropy estimates
• Randomized algorithms for analysis and control of uncertain systems. With applications
• Cross-entropy optimal dimensionality reduction with a condition on information capacity
• Principle component analysis: robust versions
• New class of multiplicative algorithms for solving of entropy-linear programs
• Minimum-Relative-Entropy Calibration of Asset-Pricing Models
• Information Theory and Statistical Mechanics
• Extensions of Lipschitz mappings into a Hilbert space
• From Sparse Solutions of Systems of Equations to Sparse Modeling of Signals and Images
• Probability Theory
• Neural Networks and Deep Learning
• Gibbs vs Boltzmann Entropies
• Good Randomized Sequential Probability Forecasting is Always Possible
• On Information and Sufficiency
• Randomized algorithms for robust controller synthesis using statistical learning theory
• On clustering validation techniques
• Extremely randomized neural networks for constructing prediction intervals

This page was built for publication: Randomization and entropy in machine learning and data processing