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» Learn .MT: A New Approach to Incremental Learning
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FLAIRS
2008
15 years 8 months ago
Selecting Minority Examples from Misclassified Data for Over-Sampling
We introduce a method to deal with the problem of learning from imbalanced data sets, where examples of one class significantly outnumber examples of other classes. Our method sel...
Jorge de la Calleja, Olac Fuentes, Jesús Go...
COLT
2008
Springer
15 years 8 months ago
Linear Algorithms for Online Multitask Classification
We design and analyze interacting online algorithms for multitask classification that perform better than independent learners whenever the tasks are related in a certain sense. W...
Giovanni Cavallanti, Nicolò Cesa-Bianchi, C...
ICALT
2007
IEEE
15 years 8 months ago
Semantic Relation Analysis and Its Application in Cognitive Profiling
Semantic web is an emerging paradigm that has great potential for the management of web content in a meaningful manner. With more and more semantic information appended to web, th...
Taiyu Lin, Kinshuk, Sabine Graf
WOA
2001
15 years 7 months ago
Implementing Adaptive Capabilities on Agents that Act in a Dynamic Environment
Acting in a dynamic environment is a complex task that requires several issues to be investigated, with the aim of controlling the associated search complexity. In this paper, a l...
Giuliano Armano, Giancarlo Cherchi, Eloisa Vargiu
ICML
2010
IEEE
15 years 7 months ago
Label Ranking Methods based on the Plackett-Luce Model
This paper introduces two new methods for label ranking based on a probabilistic model of ranking data, called the Plackett-Luce model. The idea of the first method is to use the ...
Weiwei Cheng, Krzysztof Dembczynski, Eyke Hül...