Universal Time-Series Forecasting with Mixture Predictors (SpringerBriefs in Computer Science) - Tapa blanda

Ryabko, Daniil

 
9783030543037: Universal Time-Series Forecasting with Mixture Predictors (SpringerBriefs in Computer Science)
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ISBN 10: 303054303X ISBN 13: 9783030543037
Editorial: Springer, 2020

Sinopsis

The author considers the problem of sequential probability forecasting in the most general setting, where the observed data may exhibit an arbitrary form of stochastic dependence. All the results presented are theoretical, but they concern the foundations of some problems in such applied areas as machine learning, information theory and data compression.

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Acerca del autor

Dr. Daniil Ryabko (HDR) has a full-time position at INRIA, he has recently been on research assignments in Belize and Madagascar.

De la contraportada

The author considers the problem of sequential probability forecasting in the most general setting, where the observed data may exhibit an arbitrary form of stochastic dependence. All the results presented are theoretical, but they concern the foundations of some problems in such applied areas as machine learning, information theory and data compression.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
Springer
Año de publicación
2020
Idioma
Inglés
ISBN 10 
303054303X
ISBN 13 
9783030543037
Encuadernación
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Número de edición
1
Número de páginas
96
Contacto del fabricante
no disponible
Persona responsable
CMN Printpool Inh. Mathis Neumann
https://www.also.com/ec/cms5/en_6000/6000/index.jsp

Friedrich-Karl-Str. 9
Hamburg
Alemania

Otras ediciones populares con el mismo título

9783030543051: Universal Time-Series Forecasting with Mixture Predictors

Edición Destacada

ISBN 10:  3030543056 ISBN 13:  9783030543051
Editorial: Springer, 2020
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