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1 - 3 of 3
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 Context-based unsupervised ensemble learning and feature ranking
Soltanmohammadi E., Naraghi-Pour M., van der Schaar M. Machine Learning 105(3): 459-485, 2016. Type: Article
An unsupervised ensemble learning and feature ranking method in which the combiner has no information about the expert’s performance, methods, and the data with which they operate is proposed in this paper. The method uses ba...
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Apr 20 2017 |
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A survey on context learning
Xun G., Jia X., Gopalakrishnan V., Zhang A. IEEE Transactions on Knowledge and Data Engineering 29(1): 38-56, 2017. Type: Article
This paper provides a structured and extensive survey on context learning methods. It groups context learning methods into four categories, in order of complexity: explicit analysis, implicit analysis, neural-network-based analysis, an...
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Feb 9 2017 |
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Approximation algorithms for a minimization variant of the order-preserving submatrices and for biclustering problems
Hochbaum D., Levin A. ACM Transactions on Algorithms 9(2): 1-12, 2013. Type: Article
This well-written paper proposes two approximation algorithms for the MinOPSM problem, which is the complement of the order-preserving submatrix (OPSM) problem by Ben-Dor et al. [1]. The authors provide a 5-approximation algorithm for ...
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Jun 17 2013 |
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