Universal Time-Series Forecasting with Mixture Predictors

von Daniil Ryabko

85 Seiten, Taschenbuch

Kurzbeschreibung des Verlags

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.

• Reihe: SpringerBriefs in Computer Science
• Themen: Informatik und Informationstechnologie Informatik Theoretische Informatik
• ISBN: 9783030543037
• Sprache: Englisch
• Erscheinungsdatum: 27.09.2020
• Größe: 23.5 x 15.5 cm
• Verlag: Springer International Publishing