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» Learning with the Set Covering Machine
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ICML
2007
IEEE
14 years 10 months ago
Simple, robust, scalable semi-supervised learning via expectation regularization
Although semi-supervised learning has been an active area of research, its use in deployed applications is still relatively rare because the methods are often difficult to impleme...
Gideon S. Mann, Andrew McCallum
ICML
2007
IEEE
14 years 10 months ago
Two-view feature generation model for semi-supervised learning
We consider a setting for discriminative semisupervised learning where unlabeled data are used with a generative model to learn effective feature representations for discriminativ...
Rie Kubota Ando, Tong Zhang
ICML
2001
IEEE
14 years 10 months ago
Toward Optimal Active Learning through Sampling Estimation of Error Reduction
This paper presents an active learning method that directly optimizes expected future error. This is in contrast to many other popular techniques that instead aim to reduce versio...
Nicholas Roy, Andrew McCallum
ECML
2007
Springer
14 years 1 months ago
Seeing the Forest Through the Trees: Learning a Comprehensible Model from an Ensemble
Abstract. Ensemble methods are popular learning methods that usually increase the predictive accuracy of a classifier though at the cost of interpretability and insight in the deci...
Anneleen Van Assche, Hendrik Blockeel
EUROCOLT
1997
Springer
14 years 23 days ago
Control Structures in Hypothesis Spaces: The Influence on Learning
In any learnability setting, hypotheses are conjectured from some hypothesis space. Studied herein are the influence on learnability of the presence or absence of certain control ...
John Case, Sanjay Jain, Mandayam Suraj