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» Learning and Generalization with the Information Bottleneck
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CIKM
2010
Springer
14 years 7 months ago
Regularization and feature selection for networked features
In the standard formalization of supervised learning problems, a datum is represented as a vector of features without prior knowledge about relationships among features. However, ...
Hongliang Fei, Brian Quanz, Jun Huan
CVPR
2008
IEEE
15 years 12 months ago
Similarity-based cross-layered hierarchical representation for object categorization
This paper proposes a new concept in hierarchical representations that exploits features of different granularity and specificity coming from all layers of the hierarchy. The conc...
Sanja Fidler, Marko Boben, Ales Leonardis
CVPR
2008
IEEE
15 years 12 months ago
Joint data alignment up to (lossy) transformations
Joint data alignment is often regarded as a data simplification process. This idea is powerful and general, but raises two delicate issues. First, one must make sure that the usef...
Andrea Vedaldi, Gregorio Guidi, Stefano Soatto
ICIP
2005
IEEE
15 years 11 months ago
Using appearance and context for outdoor scene object classification
We propose a probabilistic object classifier for outdoor scene analysis as a first step in solving the problem of scene context generation. The method begins with a top-down contr...
Anna Bosch, Joan Martí, Xavier Muñoz
ICSE
2008
IEEE-ACM
15 years 10 months ago
Design patterns: between programming and software design
In computer science curricula the two areas programming and software engineering are usually separated. In programming students learn an object oriented language and then deepen t...
Christoph Denzler, Dominik Gruntz