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» Strong Separation of Learning Classes
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ICA
2010
Springer
13 years 5 months ago
Strong Sub- and Super-Gaussianity
We introduce the terms strong sub- and super-Gaussianity to refer to the previously introduced class of densities log-concave is x2 and log-convex in x2 respectively. We derive rel...
Jason A. Palmer, Kenneth Kreutz-Delgado, Scott Mak...
CVPR
2009
IEEE
15 years 2 months ago
Learning To Detect Unseen Object Classes by Between-Class Attribute Transfer
We study the problem of object classification when training and test classes are disjoint, i.e. no training examples of the target classes are available. This setup has hardly be...
Christoph H. Lampert, Hannes Nickisch, Stefan Harm...
COLT
2007
Springer
14 years 1 months ago
Mitotic Classes
For the natural notion of splitting classes into two disjoint subclasses via a recursive classifier working on texts, the question is addressed how these splittings can look in th...
Sanjay Jain, Frank Stephan
FOCS
1990
IEEE
13 years 11 months ago
Separating Distribution-Free and Mistake-Bound Learning Models over the Boolean Domain
Two of the most commonly used models in computational learning theory are the distribution-free model in which examples are chosen from a fixed but arbitrary distribution, and the ...
Avrim Blum
MCS
2010
Springer
14 years 5 days ago
Incremental Learning of New Classes in Unbalanced Datasets: Learn + + .UDNC
We have previously described an incremental learning algorithm, Learn++ .NC, for learning from new datasets that may include new concept classes without accessing previously seen d...
Gregory Ditzler, Michael D. Muhlbaier, Robi Polika...