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» Methods for Dynamic Classifier Selection
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DAGM
2006
Springer
14 years 1 months ago
Handling Camera Movement Constraints in Reinforcement Learning Based Active Object Recognition
In real world scenes, objects to be classified are usually not visible from every direction, since they are almost always positioned on some kind of opaque plane. When moving a cam...
Christian Derichs, Heinrich Niemann
PRL
2010
209views more  PRL 2010»
13 years 5 months ago
Efficient update of the covariance matrix inverse in iterated linear discriminant analysis
For fast classification under real-time constraints, as required in many imagebased pattern recognition applications, linear discriminant functions are a good choice. Linear discr...
Jan Salmen, Marc Schlipsing, Christian Igel
BTW
2007
Springer
154views Database» more  BTW 2007»
14 years 4 months ago
Integrating Query-Feedback Based Statistics into Informix Dynamic Server
: Statistics that accurately describe the distribution of data values in the columns of relational tables are essential for effective query optimization in a database management sy...
Alexander Behm, Volker Markl, Peter J. Haas, Kesha...
ICML
2003
IEEE
14 years 11 months ago
Incorporating Diversity in Active Learning with Support Vector Machines
In many real world applications, active selection of training examples can significantly reduce the number of labelled training examples to learn a classification function. Differ...
Klaus Brinker
ICDM
2007
IEEE
162views Data Mining» more  ICDM 2007»
14 years 2 months ago
Exploiting Network Structure for Active Inference in Collective Classification
Active inference seeks to maximize classification performance while minimizing the amount of data that must be labeled ex ante. This task is particularly relevant in the context o...
Matthew J. Rattigan, Marc Maier, David Jensen, Bin...