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» Dynamically Adapting Kernels in Support Vector Machines
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143
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ICML
2007
IEEE
16 years 4 months ago
Sparse probabilistic classifiers
The scores returned by support vector machines are often used as a confidence measures in the classification of new examples. However, there is no theoretical argument sustaining ...
Romain Hérault, Yves Grandvalet
134
Voted
ICML
2000
IEEE
16 years 4 months ago
Learning Subjective Functions with Large Margins
In manyoptimization and decision problems the objective function can be expressed as a linear combinationof competingcriteria, the weights of whichspecify the relative importanceo...
Claude-Nicolas Fiechter, Seth Rogers
145
Voted
ICALT
2006
IEEE
15 years 9 months ago
Sharing Knowledge in Adaptive Learning Systems
In this paper we deal with knowledge representation in the area of learning design and adaptive learning. Specification of concrete instances is usually context-dependent and does...
Milos Kravcik, Dragan Gasevic
122
Voted
VISUAL
2005
Springer
15 years 9 months ago
Image Annotation for Adaptive Enhancement of Uncalibrated Color Images
The paper describes an innovative image annotation tool, based on a multi-class Support Vector Machine, for classifying image pixels in one of seven classes - sky, skin, vegetation...
Claudio Cusano, Francesca Gasparini, Raimondo Sche...
118
Voted
NIPS
2001
15 years 5 months ago
Adaptive Sparseness Using Jeffreys Prior
In this paper we introduce a new sparseness inducing prior which does not involve any (hyper)parameters that need to be adjusted or estimated. Although other applications are poss...
Mário A. T. Figueiredo