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ICCV
2009
IEEE
1019views Computer Vision» more  ICCV 2009»
16 years 11 months ago
Similarity Functions for Categorization: from Monolithic to Category Specific
Similarity metrics that are learned from labeled training data can be advantageous in terms of performance and/or efficiency. These learned metrics can then be used in conjuncti...
Boris Babenko, Steve Branson, Serge Belongie
GECCO
2006
Springer
175views Optimization» more  GECCO 2006»
15 years 10 months ago
A computational theory of adaptive behavior based on an evolutionary reinforcement mechanism
Two mathematical and two computational theories from the field of human and animal learning are combined to produce a more general theory of adaptive behavior. The cornerstone of ...
J. J. McDowell, Paul L. Soto, Jesse Dallery, Saule...
IJCNN
2000
IEEE
15 years 10 months ago
Unsupervised Classification of Complex Clusters in Networks of Spiking Neurons
For unsupervised clustering in a network of spiking neurons we develop a temporal encoding of continuously valued data to obtain arbitrary clustering capacity and precision with a...
Sander M. Bohte, Johannes A. La Poutré, Joo...
IJCAI
2001
15 years 7 months ago
Using Text Classifiers for Numerical Classification
Consider a supervised learning problem in which examples contain both numerical- and text-valued features. To use traditional featurevector-based learning methods, one could treat...
Sofus A. Macskassy, Haym Hirsh, Arunava Banerjee, ...
JMLR
2006
109views more  JMLR 2006»
15 years 6 months ago
Some Discriminant-Based PAC Algorithms
A classical approach in multi-class pattern classification is the following. Estimate probability distributions that generated the observations for each label class, and then labe...
Paul W. Goldberg