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PRL
2010
209views more  PRL 2010»
15 years 1 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
TASLP
2010
144views more  TASLP 2010»
15 years 1 months ago
Active Learning With Sampling by Uncertainty and Density for Data Annotations
To solve the knowledge bottleneck problem, active learning has been widely used for its ability to automatically select the most informative unlabeled examples for human annotation...
Jingbo Zhu, Huizhen Wang, Benjamin K. Tsou, Matthe...
GECCO
2011
Springer
264views Optimization» more  GECCO 2011»
14 years 10 months ago
Critical factors in the performance of novelty search
Novelty search is a recently proposed method for evolutionary computation designed to avoid the problem of deception, in which the fitness function guides the search process away...
Steijn Kistemaker, Shimon Whiteson
CVPR
2012
IEEE
13 years 9 months ago
See all by looking at a few: Sparse modeling for finding representative objects
We consider the problem of finding a few representatives for a dataset, i.e., a subset of data points that efficiently describes the entire dataset. We assume that each data poi...
Ehsan Elhamifar, Guillermo Sapiro, René Vid...
CVPR
2012
IEEE
13 years 9 months ago
Model recommendation for action recognition
Simply choosing one model out of a large set of possibilities for a given vision task is a surprisingly difficult problem, especially if there is limited evaluation data with whi...
Pyry Matikainen, Rahul Sukthankar, Martial Hebert