Universal Time-Series Forecasting with Mixture Predictors, Paperback / softback Book

Universal Time-Series Forecasting with Mixture Predictors Paperback / softback

Part of the SpringerBriefs in Computer Science series

Paperback / softback

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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.

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