Universal Time-Series Forecasting with Mixture Predictors

Daniil Ryabko

ISBN 10: 303054303X / ISBN 13: 9783030543037

Published by Springer, 2020

About this Item

Universal Time-Series Forecasting with Mixture Predictors | Daniil Ryabko | Taschenbuch | SpringerBriefs in Computer Science | viii | Englisch | 2020 | Springer | EAN 9783030543037 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Seller Inventory # 118540095

Bibliographic Details

• Title: Universal Time-Series Forecasting with Mixture Predictors
• Publisher: Springer
• Publication Date: 2020
• Language: English
• ISBN 10: 303054303X
• ISBN 13: 9783030543037
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 235W x 155H x 6D millimeters 235 millimeters width by 155 millimeters height by 6 millimeters depth
• Weight: 160 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

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.

About the Author

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