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SIGIR
2008
ACM
15 years 6 months ago
Learning from labeled features using generalized expectation criteria
It is difficult to apply machine learning to new domains because often we lack labeled problem instances. In this paper, we provide a solution to this problem that leverages domai...
Gregory Druck, Gideon S. Mann, Andrew McCallum
ICALT
2008
IEEE
16 years 28 days ago
Deriving E-Assessment from a Competency Model
Self-assessment is a crucial component of learning. Creating effective questions is time-consuming, however, because it may require considerable resources and the skill of critica...
Onjira Sitthisak, Lester Gilbert, Hugh C. Davis
AIS
2000
Springer
15 years 6 months ago
Early-connectionism machines
: In this paper I put forward a reconstruction of the evolution of certain explanatory hypotheses on the neural basis of association and learning that are the premises of connectio...
Roberto Cordeschi
DIS
2007
Springer
16 years 20 days ago
Discovering Communicable Models from Earth Science Data
Abstract. This chapter describes how we used regression rules to improve upon results previously published in the Earth science literature. In such a scientific application of mac...
Mark Schwabacher, Pat Langley, Christopher Potter,...
AAAI
2010
15 years 8 months ago
Cost-Sensitive Semi-Supervised Support Vector Machine
In this paper, we study cost-sensitive semi-supervised learning where many of the training examples are unlabeled and different misclassification errors are associated with unequa...
Yu-Feng Li, James T. Kwok, Zhi-Hua Zhou