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

Buch 309 von 322: SpringerBriefs in Computer Science

Ryabko, Daniil

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

Inhaltsangabe

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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Über die Autorin bzw. den Autor

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

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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.

„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.

Verlag
Springer
Erscheinungsdatum
2020
Sprache
Englisch
ISBN 10 
303054303X
ISBN 13 
9783030543037
Einband
Taschenbuch
Auflage
1
Anzahl der Seiten
96
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