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ICML
2006
IEEE
14 years 10 months ago
Nightmare at test time: robust learning by feature deletion
When constructing a classifier from labeled data, it is important not to assign too much weight to any single input feature, in order to increase the robustness of the classifier....
Amir Globerson, Sam T. Roweis
CVPR
2007
IEEE
14 years 11 months ago
Transfer Learning in Sign language
We build word models for American Sign Language (ASL) that transfer between different signers and different aspects. This is advantageous because one could use large amounts of la...
Ali Farhadi, David A. Forsyth, Ryan White
CVPR
2007
IEEE
14 years 11 months ago
Unsupervised Learning of Invariant Feature Hierarchies with Applications to Object Recognition
We present an unsupervised method for learning a hierarchy of sparse feature detectors that are invariant to small shifts and distortions. The resulting feature extractor consists...
Marc'Aurelio Ranzato, Fu Jie Huang, Y-Lan Boureau,...
ICDE
2008
IEEE
100views Database» more  ICDE 2008»
14 years 11 months ago
OptimAX: efficient support for data-intensive mash-ups
n a node with a b child, and abstract away some details of the AXML notation [3]. A. ActiveXML documents ActiveXML documents are XML documents including some special elements label...
Serge Abiteboul, Ioana Manolescu, Spyros Zoupanos
NIPS
2004
13 years 11 months ago
Learning Hyper-Features for Visual Identification
We address the problem of identifying specific instances of a class (cars) from a set of images all belonging to that class. Although we cannot build a model for any particular in...
Andras Ferencz, Erik G. Learned-Miller, Jitendra M...