This important new text and reference for researchers and students in machine learning, game theory, statistics and information theory offers the first comprehensive treatment of the problem of predicting individual sequences. Unlike standard statistical approaches to forecasting, prediction of indi
Prediction, learning, and games
β Scribed by Cesa-Bianchi, NicolΓ²;Lugosi, GΓ‘bor
- Publisher
- Cambridge University Press
- Year
- 2009
- Tongue
- English
- Leaves
- 408
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Subjects
Algorismes computacionals;Aprenentatge automΓ tic;Jocs, Teoria de;Llibres electrΓ²nics;Aprenentatge automaΜtic
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This important new text and reference for researchers and students in machine learning, game theory, statistics and information theory offers the first comprehensive treatment of the problem of predicting individual sequences. Unlike standard statistical approaches to forecasting, prediction of indi
This important new text and reference for researchers and students in machine learning, game theory, statistics and information theory offers the first comprehensive treatment of the problem of predicting individual sequences. Unlike standard statistical approaches to forecasting, prediction of indi