Title :
Universal prediction
Author :
Merhav, Neri ; Feder, Meir
Author_Institution :
Dept. of Electr. Eng., Technion-Israel Inst. of Technol., Haifa, Israel
fDate :
10/1/1998 12:00:00 AM
Abstract :
This paper consists of an overview on universal prediction from an information-theoretic perspective. Special attention is given to the notion of probability assignment under the self-information loss function, which is directly related to the theory of universal data compression. Both the probabilistic setting and the deterministic setting of the universal prediction problem are described with emphasis on the analogy and the differences between results in the two settings
Keywords :
information theory; prediction theory; probability; reviews; deterministic setting; information theory; overview; probabilistic setting; probability assignment; self-information loss function; universal data compression; universal prediction; Control theory; Data compression; Entropy; Information theory; Machine learning; Natural languages; Operations research; Predictive models; Statistics; Stochastic processes;
Journal_Title :
Information Theory, IEEE Transactions on
