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ECML
2007
Springer
16 years 10 days ago
Fast Optimization Methods for L1 Regularization: A Comparative Study and Two New Approaches
L1 regularization is effective for feature selection, but the resulting optimization is challenging due to the non-differentiability of the 1-norm. In this paper we compare state...
Mark Schmidt, Glenn Fung, Rómer Rosales
ECTEL
2007
Springer
16 years 10 days ago
Categorizing Learning Objects Based On Wikipedia as Substitute Corpus
As metadata is often not sufficiently provided by authors of Learning Resources, automatic metadata generation methods are used to create metadata afterwards. One kind of metadata ...
Marek Meyer, Christoph Rensing, Ralf Steinmetz
ISMDA
2003
Springer
15 years 11 months ago
Inductive Learning of Simple Diagnostic Scores
Knowledge acquisition and maintenance in medical domains with a large application domain ontology is a difficult task. To reduce knowledge elicitation costs, semi-automatic learni...
Martin Atzmüller, Joachim Baumeister, Frank P...
ICCV
2011
IEEE
14 years 6 months ago
Domain Adaptation for Object Recognition: An Unsupervised Approach
Adapting the classifier trained on a source domain to recognize instances from a new target domain is an important problem that is receiving recent attention. In this paper, we p...
Raghuraman Gopalan, Ruonan Li, Rama Chellappa
IJCAI
2007
15 years 7 months ago
Constructing New and Better Evaluation Measures for Machine Learning
Evaluation measures play an important role in machine learning because they are used not only to compare different learning algorithms, but also often as goals to optimize in cons...
Jin Huang, Charles X. Ling