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» Semi-supervised Learning from General Unlabeled Data
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CVPR
2007
IEEE
14 years 1 days ago
Improving Part based Object Detection by Unsupervised, Online Boosting
Detection of objects of a given class is important for many applications. However it is difficult to learn a general detector with high detection rate as well as low false alarm r...
Bo Wu, Ram Nevatia
GECCO
2005
Springer
232views Optimization» more  GECCO 2005»
14 years 1 months ago
Factorial representations to generate arbitrary search distributions
A powerful approach to search is to try to learn a distribution of good solutions (in particular of the dependencies between their variables) and use this distribution as a basis ...
Marc Toussaint
CORR
2008
Springer
99views Education» more  CORR 2008»
13 years 8 months ago
When is there a representer theorem? Vector versus matrix regularizers
We consider a general class of regularization methods which learn a vector of parameters on the basis of linear measurements. It is well known that if the regularizer is a nondecr...
Andreas Argyriou, Charles A. Micchelli, Massimilia...
DASFAA
2007
IEEE
139views Database» more  DASFAA 2007»
14 years 2 months ago
Self-tuning in Graph-Based Reference Disambiguation
Nowadays many data mining/analysis applications use the graph analysis techniques for decision making. Many of these techniques are based on the importance of relationships among t...
Rabia Nuray-Turan, Dmitri V. Kalashnikov, Sharad M...
BMCBI
2008
219views more  BMCBI 2008»
13 years 8 months ago
Classification of premalignant pancreatic cancer mass-spectrometry data using decision tree ensembles
Background: Pancreatic cancer is the fourth leading cause of cancer death in the United States. Consequently, identification of clinically relevant biomarkers for the early detect...
Guangtao Ge, G. William Wong