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200106 ||| eng |
| 020 |
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|a 9780262301220
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| 050 |
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4 |
|a Q325.5
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| 100 |
1 |
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|a Sugiyama, Masashi
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| 245 |
0 |
0 |
|a Machine learning in non-stationary environments
|h Elektronische Ressource
|b introduction to covariate shift adaptation
|c Masashi Sugiyama and Motoaki Kawanabe
|
| 260 |
|
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|a Cambridge, Mass.
|b MIT Press
|c 2012, c2012
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| 300 |
|
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|a xiv, 261 p.
|b ill
|
| 505 |
0 |
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|a Includes bibliographical references and index
|
| 653 |
|
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|a Machine learning
|
| 653 |
|
|
|a Adaptive control systems
|
| 700 |
1 |
|
|a Kawanabe, Motoaki
|
| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b OUP
|a Oxford University Press
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| 490 |
0 |
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|a Adaptive computation and machine learning / Adaptive computation and machine learning
|
| 856 |
4 |
0 |
|u http://dx.doi.org/10.7551/mitpress/9780262017091.001.0001?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
0 |
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|a 006.31
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| 520 |
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|a This volume focuses on a specific non-stationary environment known as covariate shift, in which the distributions of inputs (queries) changes but the conditional distributions of outputs (answers) is unchanged, and presents machine learning theory algorithms, and applications to overcome this variety of non-stationarity
|