Reframing in context: A systematic approach for model reuse in machine learning
Reframing in context: A systematic approach for model reuse in machine learning
复制标题
DOI：
10.3233/aic-160705
复制
发表时间：
2016-11
期刊：
影响因子：
--
通讯作者：
J. Hernández-Orallo;Adolfo Martínez Usó;R. Prudêncio;Meelis Kull;Peter A. Flach;Chowdhury Farhan Ahmed;N. Lachiche
中科院分区：
文献类型：
--
作者：
J. Hernández-Orallo;Adolfo Martínez Usó;R. Prudêncio;Meelis Kull;Peter A. Flach;Chowdhury Farhan Ahmed;N. Lachiche
我们感谢匿名评论者的评论，这些评论有助于显著改进本文。这项工作得到了REFRAME项目的支持，该项目由信息和通信科学技术ERA-Net长期挑战欧洲协调研究（CHIST-ERA）授予，由英国（EPSRC，EP/K 018728），法国和西班牙（MINECO，PCIN-2013-037）各自的国家资助机构资助。它还得到了欧盟（FEDER）和西班牙MINECO资助TIN 2015 -69175-C4-1-R以及Generalitat Valenciana PROMETEOII/2015/013的部分支持。
We thank the anonymous reviewers for their comments, which have helped to improve this paper significantly. This work was supported by the REFRAME project, granted by the European Coordinated Research on Long-term Challenges in Information and Communication Sciences Technologies ERA-Net (CHIST-ERA), funded by their respective national funding agencies in the UK (EPSRC, EP/K018728), France and Spain (MINECO, PCIN-2013-037). It has also been partially supported by the EU (FEDER) and Spanish MINECO grant TIN2015-69175-C4-1-R and by Generalitat Valenciana PROMETEOII/2015/013.