Machine Learning in Non-Stationary Environments: Introduction to Covariate Shift Adaptation
(Part of the Adaptive Computation and Machine Learning Series)
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Theory, algorithms, and applications of machine learning techniques to overcome "covariate shift" non-stationarity. As the power of computing has grown over the past few decades, the field of machine learning has advanced rapidly in both theory and practice. Machine learning methods are usually based on the assumption that the data generation mechanism does not change over time. Yet real-world applications of machine learning, including...
Format:Hardcover
Language:English
ISBN:0262017091
ISBN13:9780262017091
Release Date:January 2012
Publisher:MIT Press
Length:261 Pages
Weight:1.10 lbs.
Dimensions:0.7" x 6.4" x 9.3"
Age Range:18 years and up
Grade Range:Postsecondary and higher
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