Machine Learning in Non-Stationary Environments - Introduction to Covariate Shift Adaptation

Informationen zum Autor Masashi Sugiyama is Associate Professor in the Department of Computer Science at Tokyo Institute of Technology. Motoaki Kawanabe is a Postdoctoral Researcher in Intelligent Data Analysis at the Fraunhofer FIRST Institute! Berlin. Klappentext Theory! algorithms! and applications of machine learning techniques to overcome "covariate shift" non-stationarity. Zusammenfassung Theory! algorithms! and applications of machine learning techniques to overcome "covariate shift" non-stationarity.

Dettagli sul prodotto

• Autori: Motoaki Kawanabe, Motoaki (ATR Brain Information Communication Research Laboratory Group) Kawanabe, Masashi Sugiyama, Masashi (Associate Professor Sugiyama, Masashi Kawanabe Sugiyama, Masashi/ Kawanabe Sugiyama
• Con la collaborazione di: Francis (INRIA - Willow Project-Team) Bach (Editore)
• Editore: The MIT Press
• Lingue: Inglese
• Formato: Copertina rigida
• Pubblicazione: 30.03.2012
• EAN: 9780262017091
• ISBN: 978-0-262-01709-1
• Pagine: 280
• Serie: Adaptive Computation and Machine Learning series; Machine Learning in Non-Stationary Environments; Adaptive Computation and Machine Learning series
• Categoria: Scienze naturali, medicina, informatica, tecnica > Informatica, EDP > Tematiche generali, enciclopedie